{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 6. Mom Divergence"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Divergence Index(Divergence)\n",
    "长期动能上涨，短期动能下跌。\n",
    "$$\\text{Divergence Index} = \\frac{10_{day} momentum *40_{day}momentum}{(40_{day}\\text{ standard\n",
    " deviation of price changes)}^2}$$\n",
    "Enter when Divergence Index falls below –10 and mom40>0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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HXjii3MLGFzVTfv3uCCpcNcn0N5B3X7aduqhonOc/sNHjAflyGpKn0+/dk4A7\n+SlcX75jEUFWLUH27sH99fugTp1zywNQPxZqhkOr9phLb8QZ8xLOrQ9CXGOch5/Fmfw59OqHfDMd\nWbIA2fm3zUNYWF23brQxAqo4HbE7QvLHrwA4l99awTWpYvLOeT5cxyK2Efw5D3G9pR66P5q5P3yJ\n/Po9AOaCf+GcOsh/TA7uh9RkZP9eTN7OdjFIRhokH4TEXXYKZv1YzIBzMY2b+c8xx3TH1IvBNGiE\n/P6LjQ7WvjPOVbch3U9A5s6yH6qrlyLZ2cV+iisiuI/fA5vXB5U7L31coU+CiyJpqbh32VFJM+xy\nnHMvquAaKaVUyciGVbj/s+mJanTrhbdGTTz3PIb3+iEANmjWjI/syds2YS69CWfAuYELVJYH4AVM\nzcsdeZRN65BTzkQW/2bz0MU1OaJbyYEk+/O7z+Cia47oWuVF9iUi82bZCKfRdYr/utRkZPqbENfY\nLv3Yvxdq18W55k7o2AVTMxznvieQH79CPngN9yYbO8Gc9w+Slv6ObNsEC+fgenOQ336GrRsDF2/Q\nEOehp+36/PAIPHkSw/s1bo4nb5T1sy/E/XMe7ouP2YIOx9rlH2kpEBEJGRmwZSOybw/y3su2Lmec\nj3PJ9SX9k1Uape7YpaSk8Ndff9G6dWvq1Cn+//TqRHZuQ+b9gDk5Pn8kJFW0vBGl2nUq+ty4xnYq\nR9JeDRdcQrJoLjLtVf++Oe3s4BMy7Bx0WbkYc3J88a+7awfuQzfZnVbtITwSZ+wkTM3woPP86ymb\nt4bffwHAueR6TGSUnc7Sb6A/r558/UG+6Zgignz6FvLNxzj3P2mncu7eaUfnDunUAbBji61PZbRm\nmX9TFs4B7dgppaoQST7o79TRsi3RF11NRqJv7VxYDftZ3ao9eDz+6Zem74AKqu1h5D4kbtoyeHmA\nj3vDUADMxdce0WgdgOnWB3l/MtSpd0TXySUHk5C5P2AGDMZERB7ZtVy3wPVn7rTJsHg+8vl70Lsf\nplYdZM9OiIzCufE/+V4jGemwewfu1Odh619Bx8w/bwwKlmMcDww8H5nzvf9vL199gBcwpw6yU3k/\neM2ee/ZwqF0X0lMxpwwqUScTwLTpiPPABNzpr2MaN0dmz8S9/zpIPlD432TJAuSCfx3x37ailKpj\nl5SUxPjx4+nduzdTp05l1KhRvPvuu2zfvp2ePXsyfLjN+TFp0qRilVVV7uvPgMcmoFQlY8LCMEMv\nw7TtiIlCX7S6AAAgAElEQVSJK/rc2EZ2pGdPgnbsSsid/0tgp01HTO3gN0Xn8ltxH7gh3xoIAFm7\nAnf8Azh3PII5JNqrm6ezyJYNNihOnk6dM/KhwAcnYM4c4l+EziHTcJxTB+Gd9wOydnng3jk54PEg\nP89AvvnY3nPcffnq6Dw0EZq1hD27cB++Bfn2E8yN+c+rSLJuJe4302HFIn+ZaX9s+ddj0zrcyU9B\nUiLmrAtxhl1e7nVQSlVNkp2NzPo8T0lwZ8d57n0wBuM4OOOm4D50s42GXFm/HPs6Js6QS3E/eh32\n7rblbTtB7tKAXn3tVNMjZOIaY/oOCI6wWQLi9WI8HmTHVtzXJvpHseSTt/KvCyzJdbdvsR31yEiI\na4KJicNcfbuN3rl4vl2nVjMcFs0j7wRG+fU7GwMnPBxz4umwagnuG8+Ab2TSXHSN/U6RvB9z0TUF\ndoyN4+D89xnYsgHZvhlSkqnbuRvJbY5BBv8DmTMT07o9pkcBo3IlZNp0wHPvE3YaZlqqf6ad//iZ\nQ+3v3O4YTN+BkJZSedttMZSqY7dt2zauvPJKOnbsSEpKCitWrMB1XcaOHcuUKVPYuXMnW7duLVZZ\nkyZHNsRdUWT7Vti83j7NOUzHRBXMOe8fxTsxrjFgE5qbY44rwxpVQ5vWYU7oj3P93QUfrx9rP+D2\n7sad/zPmmOMw9WKQtBTc8Q8AIHNnBXXsJCcH1i0Puozpc3Lwfm5E09z9sBo4tzxg8wYVMJ3WNGiI\nLPgF99UJdvH9R2/YHIdpqYX/bh4PppUNqS2N7PuI/PEr0u8MTLfehb+uHMmiubgv/y9/+c8zkP5n\nY5q3Du39du9AZkzHnH2hfTqZkQ4Jf0N6WiBYESAzPkK69PLnXlJKqcK4835A3ngW8j6QcoMfBuZN\nXWPqNcB5blrljkSYW7d6MXjGTcH73KOw/A+cIZciyfuRGdNxrrztiEfr/OrGQGYG3uuH5J+eWgT5\nay3uE/fav/2+3bAvMfiEvzchtWojv36PiR9S7BEt9/P3kK+m2Z30VNiXiADmxP64rzwJgLnkOky/\neBvlNOUg1K2PO+kJ5O2XAvXLzTcM0KAhpvsJOIMuKFYdTFiY7Uz51tyFx8aSnJiIaRBXJsHUjDFw\n/d3Qsq2NcBpdF1mzDNO7b/D3ktp1Q37v8lSqjt1xx9kv16tWrWLjxo2kpKTQt29fALp27cqaNWvY\ntGlTscoO7djNmjWLWbNmATBu3DhiY2NL95sVU1hYWInuISKkf/0Rya89A0CDsy/AU79ka5NUyUj9\neuz2eIhITKCWETwNKm9HuqTtqSylffUhyQf2EdW2A9FF1CmxUTO8vjURAjT6dB4HJ08l3XdcFs4h\n5o6HcXzpCA688DgZWVnUvftRDkx4GIDY/oMOHzzozPMKPZR+Un8OLvgF+f0X/5TNml16kLV0IeEn\nnU70pTcgmensu/daPM1aUvfuR3Fq1caT5/faHRFl1/1NfY6YFz/AqeDcNRnzf+HAIZ26uPe+J/GG\n4UjKQaITE4js0afIaxS3PYk3B+MJI+m5R8havoiaWRnUvXcsu68PPG02depR+/JbyPl7M2mfv4dn\nxofU73tkQQFU1VKZ3p9U1bF7+pt2Y8MqPE2a4935N+HNWlbp9pRYoyZeoF7jJtSIjcV724OkfvQm\ntfudbtdpnxfaqfLZZw1l37d29om89zL14wcX67vj/tefJhNgwyoAPI2a4t21gzp3jebg06Nxx97l\nPze6cVOizguOzp6zfQueuMZBM2q8SXtJ9HXqPM1aUf/R5znw9CiyD4k62WDguXjqxUDjxv6yzFv+\nj7Qv3qdmt96kvGsDstW+8R4izzjviPPSllt7uvymwHabtmV/v3JW6jV2IsK8efPw+IaAY2LsWprI\nyEgSEhLIzMwsVtmh4uPjiY8PrPVJTEzMd04oxcbGluge7lfT7JxjnySvQBnXUQExcaTPmE76jOmY\nG+7FdO4OKcm4n72Nc/WdIF7km08wnY+r0FG9kransiIrFuH6Hj6kH3dCYB1EAbz1YgJhnYE9G9bh\n+qY/0r4zbFjN3iV/YDp2sdf94Sto3JzkjsdhbrgPdu9gb3IKJKeUvr5demPOHo74PvjofgLekQ/h\n7NtDdq3a7A+PgMhonIefRerW40BtXw6hPL+XefgZ+OFL3B++ZO8fv+WbPlre3N990z26n4Bz4RVg\nDPtS0zGjn0fuuZLkvzeTsuQPaNYKYwzy52+409/AnHsR5tiemJjYw7YnWbEI99lH7E6Pk2C5ne6Z\nufBXdl98etC5ZuzLpEZGQY+TMJHRZE+bzO4LT7ZTZQYO1hycR4HK8v6kqg5xXZtU2scdMBindl2y\nO/cgJyenyrYnb/0GsH0L+5NTMImJgAcuupa9Bwpfe3UkJCL4QWPinVfiGf9m4LiIf12fM/lzO0pW\nPxZ36UJfkA/fevhRz+FkZJASVctGl9y4xn+NlO3bSMvz/8P9YAoy6wu7Lu6ex6BBQ2TFn8gv34Dj\n4DwwHmnRliQXuOMRnKULcT96HXPWMJxTB5GU4+b/ftuqA/z7YdIB55juEB5JWv0GpB04eMR/I31/\nKlrTpsXL/Vjqjp0xhuuuu45p06axYMECsnz5OTIyMnBdl4iIiGKVVTWmx0nI2hWwZpkNq6rKR2wj\nu8YOkMlPwUkDwJsDi+bhLppng3P8vRmZ8SHOix/lC+JxNJH1q/xf9p3HXrHpIoqyOjjRrPz4pd3o\n1A3nipG4D96IbNkADZv4r2vOOA/jOJjjTwlJnY0xcOEVNpCO60KHrrb8kGnORYXJNnGNYfDFyE9f\n474+0a4NrMCw2nIwCRo2wTPyoaByU9d2SuXz9+xDovadbSQ531Nxmfo8Anhe/QLvvkREpMBRNRHB\nfT/PWscl8wFwbh+N++xoW9buGJxLb4IDSZg8+SLNKfHItMn2Oh+9jnz0uu1gnjMC58T+ofkDKKWq\nvsTgHLLOgMEVVJHQcq69C1n6e1AU57JkwsIwZ12IzPzEFuTJ6Qb4IzICyK/fI2+9ADGxkJaKuWIk\npn4DZMc2OyrmGxnz3P8kkpUJibtwJz+F/LUWSU2GmhGYGjVscBIAY3DH3Blcn0tvxBwSaMx0Px5P\n9+OL/zs1bl7sc1X5KVXH7rPPPqN+/fr079+ftLQ0hg4dypo1a+jYsSNbtmyhadOmNGjQoFhlVY1p\n3hrP3WMruhpHHdOzr80Z6COJCZg2HQMn5M09sn4VVPBoTUUQ14VVi/0LtJ2HnsY0PPwaVvOvW5B3\n8syZ/+ZjaNIC5+b7IcJ2BuTD1+yC7bAwnOvuhoLCDB8hY4wddTqSa9SuixkwGPnhS9xHb8eZ/HmF\nTDWUrExYtRRTnA/JDauRDavttu8BBYA7dxaJbz4H2EhhZsRVmLw5Hzevh907MP3OQOb9AM1b49z/\nJCY8AufJNyAzo9AvLSY8Auf2Ubi/fAtLFtjC7VuQKROQzsdh6tQv+PfyemHVEmjbEVk0D9O0RYUE\nglFKlZM8o3VmxNUVWJHQMtF1ShQJOiT3HHY55tRBuKNuBa/XH5FS0lKRn7/xnydvvWA39iVCVC1M\nl16YmFhM1/xrx03NcGja0n5H+moa7h2XBR8/Z4QNRPbVB4HCVu0xpxdvjZ+qekrVsYuPj2fixIn8\n+OOPtGjRghNOOIFRo0aRlJTEkiVLeOwxmy+iuGVKHY4z4Fy8eZ5oUaMmpB4y9a9rb1ixCPeZUXhe\n/aJ8K1jBZNsm5OsPkUVzbUHLdvmexhXGHHe8jXjlOHa0DF9HIje/YI+TYMl8ZP7Pdppg75MLvVZl\n4FxyPd5VS+z00sx0f+e0PMnS32145n5nFHjcGflfZMUfyP59du1ESrItv2IkpKfiThyF+Dp1ADLn\nOxvV9NRBuPN/Qj583X7hchwbwGnE1VAr2h+swBRj7Ybp2htP1942pcRvP0LC38g3HyOLF9jE9Yf+\nTiLI5+8i30wPlAHOzfdjDkk4r5SqJlJ9703//i90K3pNsCqa8XigUVPMsMvtDI3N63G3bfIHAePY\nnrBqsd1u3AwStmP+dSsm5vDrzswpZyLrVviTrfvL23aEDl3g4H7MoGE2LUXderq2uhozUlQa9hJI\nSUlh2bJlHHvssdSrV69EZUXZsWNHKKpXKJ3TW3V48wSCoHZd+wZVLwY2rQPAeeVT3Bt9yS4vuxnn\n9HPKvY4V1Z6891zpDzUMYC67CaeYT+TE9eK+8iTOmUP9OYrMVbfjnGw7JZKRhvvvSwBwXvjw8EFS\nKgH31++Rqc/jjJuCqYAUGd6JoyBhG84TU4oVGU5EIHGXf9qs97G7YfN6oi+/mdRsr3/apDl1kO2E\nxcTBvj2Ynn1xbrg3JHUWEdyHb7FPiVu0gZwcTKv2mBNOg3oxgbyFh/J4cCa+GzTVU1VO+nmnSsr9\n/F3k649wxr+RbyRf21PpuD/PQN7N86A6N+9f736waB4Azs3/B1G1oFO3EnXCJCMd/loDrTtAZK0q\n1YHT9lS0Ml9jd6jo6Gj69etXqjKlisN5fDLy5ftIerp/PZEZOBjxdeyM48F5bhrubZcg705CTo63\n0a2qKcnOBnFthy43f8xJA6BdJ4rbqQP7d/Pc/H/BZXkiSpqIKJy7xtjRoSrQqQObGF0A9/7r7BTG\nQcNK/QGXN4GrrFlmR0OjaiF7dyPfTLeBfJq19k97dH/8ClYtttNuihnu2xjjT+sBYE4/B3lvKxGn\nn0O6C961y2yy2DnfAeDcNw5q1Q6E7A4BYwzO0MtsqGvfgnzZsgGZ/S3kGZFz7n/Srm8VkOULkZmf\n4t52CeakAZgr/21DWCulqjzxepHffoKY2EKnZ6uSMy3bBeWFM6edBakpmMEX25gBAA2blCodjomI\ntCN/6qiln8CqyjBxjTHX3GlzrN3u69i174xERNrgKhA8apCWAnWr54eR+8qTNslmg4Y2CmhYDZyx\nk458dKpBQ5uo9dBF1Z27H9l1y1vLdv5Nmf6mXZ+5cjHO7aMKXKdQEMnMxH3wBttpdhzo1M0faMZc\neAXyyVv2vF++hbjGeB6fjKxdjkybAt1PwJx9Yamr75wcj/QdiCcmFhITcS68AnexbfPUa+APwBJy\nvfphzv8n8t2nmLMvRBbNs2v+/pwHjZrhPPBU8Dq/Rk2RmZ8CIPN/sjmJKmCkXCkVerLgF/t5oPku\nQ6tpC/+mc984TIfAOmVz7kXIjI9AA5OoUgrZVMyyolMx1aFEBHf0v+Hgfpyn34bsLDDGn0PFXTgH\nmfwUzugXMM1almvdyro9iQjuI7fB9i1B5WbAYJxLbzzy62/diCRsxznhtCO+VkWTTetxH8+fmD1v\nQBXJzrYjkZ78SdPdL95DvpxW9E1iYv0JY82gYch3tpPjPD8NE4K1fXnbk+xJsJHUGjQq1hq6UPGO\n/jds34I57Sycy2/Nd1xcL2Rn4468GHPS6cj+fXZ9Z4M4yMzAOXt4udVVFU0/71RJuG8+i8z9AWf8\n1AIfJml7Kj13ygTMCadhjgsOsCUi4LoFfiZVd9qeilbuUzGVKi/GGDyPvBAoOCS1galrp+Gxbw+U\nc8euLMiBJEhKxLTuYKMf+jp15rx/+CNdmW7FG4U6HNOyHSbPaFdVZtp0sJEfc/O8+bj3X2fXp/Ud\nYKcZdTgW564xQXncZPmiQKeuSQt/nj/n9lG4r06AtBTMoAsww6+C3TtwR9/m79SZsy4MSacu3+8T\n1zhoumZ5cW4bhfz8NeasgkcgjeOBcA906YnM/xnwTVn1cTPScS74V3lUVSkVQrJ+tZ19UE1nvlQk\n57r8Dx3BNy3/KOzUqdDRjp2qfnzz0mXrRrsWqG794NQIVYj73Wc2xxjgPOMbQYqujTl9MGbwRZjT\nzraJTIs5vfCo06qDf9N5+m3cuy63HX6wnTqA9atwX3kKz60P2PKcbNx3XgTA/PMGnIHnISsW2UiX\nx/bEeeJVCAsL5Eps3BznoachKRG69Cr2urqqwsTEYi688vDnde6OrFwM4RGQmeEvl68/xK1R00Zk\ncxzYvB7T7phCryN/b8L9+C0b0bROPZxLrsfUK78RSqUUSNJem07ltEEVXRWlVAlox05VOyaqFsQ1\nRrb9hXz2DkCVTH8gKQf9nToAmfEh7N0dHF6+fgP7nyqQqV0H55VPITMTExmF8+QbuP+9GRo3xzRq\nhvz+C6b3yciyhUh2FjLtVWTJAhsa+sp/45xypr1O196BtXlRtfLfp3lr/wOFo5Xp1Q/5Y65dD/jT\n17B4Ps69j+M+9QDy2Tv+f4vgy7FYQDoO2bgGd9x9wWXH9rAPMEJIMjMx4eGHP1Gpo4z76gRk7y6b\ngsXjwRxhblGlVPnSjp2qlky7Y/zTwqoiWTQPd/KTAJjTzkZmf4t89xnUj4XuJ1Zw7aoW43jAF1TH\n1G+A87/X7chRzXDMFSORn76CRXOR7z9HZs8MvO7YHhVV5SrJxDXG8+AEADydu/ujieadMpxLtm/x\nd+zc2d/C+lWYwf/AfWGMPaFXX/jzN3vuwl+RU88KSdhuWTQX9+X/BZU5tz6I6VH4vylxvcgnbyEL\nZmNOOh1n+OFHL6sa2b4F97N3Ma3aYVq0hbadMLXrVHS1VDmSPQm4H0yBpb/7y8wJ/TGNireuRylV\nOWjHTlVLZviVQR077/VDcEY9V6rwwaEkmRnI4t8wJ55e4BdVEYE/5wV9+XQuvwXvwf2wZD6mY5ej\nclF1KOVN5YDHg/im+cmnbwfKe56EiYkr55pVL7lTUp2hlyFnDQPHY0dE53yHvPEsblgNTOceyNsv\nASBbNkJKMmbE1Zgzh2IcB3fyU8jCObg3DLXXeuQFTNPSrZuVjDTct17IV+6++BjmjPNxLrk++Pxl\nC3FfHQ8Z6YGybz/Gbd4a060PeHOQxfMx/QYGrc+samTzetzH7wVxkSXz/WHYnZc+rtbpYo5W4rqw\nbgWSfBDT80RMWA0kNQX30dv9bd0Z/QLy+2zMSf0ruLZKqZLSjp2qlky9Bpj4IciswBRM97G78Ez6\npAJrBe6Up20HrWnLoJD8ueSNZwJrv/JwrrsL+WAK5sTTy6GWRxfTpaf/y6zpOxBz3sV2ZFSFTG4w\nGXPFSKTPKbgTH0ZeHY/kXWu3cxtERWPih/g7hWbE1TZyqS9vpTtqJM5z04qdDF0y0pBfv0e+mAbp\nqYAvB6AxdnRi83p73g9f4qalYP51C6ZmuE3KnGeU0Yy4GtO5O+4T9yJTJgTloGLNMkyIksSXN3Fd\n3C/eB8fBue4eaNkWd/J42LIB96XHbG6t+CH+KLmSnQWesGq3jrS6Eq8XUpNtyoK69ZGfZyALZgfW\nGYOdln7S6ZCRjjnjfBupsVlLzDANeKRUVaTpDjS8arXl/jQDee9lO+3OdQEbgCR3xEZSU+zi8BAG\nVjlce/JePwQAc/ypmPP/iWkSyFWTd32Ruep25NO3MeeOwBl4XsjqpwomKxYhyxdhhlwaPKJXwarr\n+5NsWIX70Ruwfatdx9O1t13veOZQnIuvzXe+O/8n5LWJdiciEue/z2AaNgm+Zm7ahWdGQ526mOOO\nR958LugcM/zKoPQLsnc3/L0F98WxIIK57GbYvB6ZO8ue0P5YnHsfs9N5sQEl3Puuzv8LxTWGPQlw\n3PE4N9xXadfvxcbGsmf3buSzt5FvPvaXm/P/iTPkn4BvWubofwe9zsQPhaYt7OiquDivfOr/mxRG\nMtKR335E1iyHbX9hzrsEp9/A0P9SqkDy5zzcSePyH+jaC3NCf9i1Hfn6w0B5rdo4E98p0ZTn6vr+\npCqGtqeiFTfdgXbstCFVW5KRjsz4EHPORfD3Ztwn78ecOgjnipEAuNPfQGZ+inPjfZg+p4TknkW1\nJ9mwGvd//wkUdDgWz332g1dcF/exu2HrRoiujWfiuyGpj6raqvv7U27OJpIP2KTogy/G1Kpd8Llb\nNiAb1yAfvg6t2+O5/8mg496nHoB1Kwp8rbn0Jszp5xT6pVWyMnFvvSiozLl9FHToggmPyF9nrxd2\nbIHwSNzRIyEnJ3Cvf1yHEz/ksL97eXN/n43z7cd4t23Kd8x59j1/4nkRwX3uUVixqNBrOf/+rz//\nlojYKbS+NXmSkw2Ju+zshC0bgl9356MhW7sqG9dAw6ZHtBZQErZDbCNMWPWYvCSZGfZBSVgNvI/f\nA5s3QKMmkLDdntC5O567xuQ5PxN5/xX7IKNXPzw331+i+1X39ydVvrQ9FU3z2KmjnomI9Idpl/ad\n7c8dW+3P1BRkps075r79Ek7bYzAxZTv9zv30reCC9HTc+T9jmrSwX263bsScezFm0AVlWg+lKgt/\nzqZ6MZgCRuqCzm3VHtOqPW7KQeTLabjvvmz/rTRoCEhQp8559EVk4Rxkzvc4tz4ALdsVORJhaoZD\n4+awawfOTf+xKVIKSclgjIGwMP9UaueJKcjcWZhOXXE/fw/5YAreT9+CrCzMiKtxzhpW8j9MiLmz\nv0XefgnTOpD+wwwahjnvH5Ce6u/UgS9P6O2jkN07kEXzMI2a4r72NGRlQadusHY57vNjoGtvTN16\nUDMC+elrO7p53V24D99izwXo1A3TqRumx4m4j96O/PZTSDp2snY57vgHbX0HX4xp3QHT40Qk5SDu\nmDvsHMMWbXCGXpovL6fsSQDHQT56A1k0117jkJHcqkJycuzfPnEX8vtsSDkYdNyMuArnrAuR5AOQ\nmpIvgrIJD4cr/42JHwKaq06pakFH7PQJwVHDffM5ZMkCnPFvwrI/cCc9YQ+ER0CbjvZp8hGuHSms\nPUnC33Z6U5uOsGF1vuPmnBHIN9NxnnpDc3YpP31/yk/WLMOd8FBwYY2akO3rTHg8eF7+tOTXTU2G\nsBr5RuhKdI2Ug7j3XhU0gkf7zlC3Ps7Qy+xDHECWL7L5KMs4v6bk5MDG1f5OUOxrX7AvJRU2rcN0\n6Vn86/iCOtGpGzLvB2T1Uli1xD/FvUANGuI88BSmju0wuG88iyycg7nqNsyxPTDRpR9p8056wh81\n1S9PJFW/dsfgjHwIImthPB5kyXzcFx8v8JrO/z2Fadup1HUqb5KagnvHpfkP5OaRrFUb57GXCx0B\nDwV9f1KhpO2paDpip9QhTJ+TkbmzcB+9A3OqTbrqPPoismE18tYLsPg36H1ymdxbVi4Grxfn+nsg\nPAKZ8ZFNX5B7/JvpENdYO3VKHU7HLnYkPjUZmekLhuTr1DkT34GszFJdNhRfgE10HZzxbyF/zgNj\nkKnP+x/kuIvmYS74l51CuPwPe/4/rsWcOCAwjXHpQtwfv8Q5/58Y3ywD8EUy3Lsb0tOQZQvtaGKn\nbnAgCVNIHkvJSMP9762wf6+91+nn4ImJxbhACTp14Bul9L03mkHDYNAwJCMNVvyJO+sLCI+EVYvB\nOJjhV+CcdWH+a4y4Clk83wbNCauBM/r5UoXSl83r4c/fMGecbzsxKQdtmpI/f4OOXcB1MZ262ajI\nG9fg3mmDgJgzh9rRLYBje2DadLT5Eb05uBMewn1hLM5DE6FOXfB6i+zgS04O7iv/s3lF//NkkWsq\n5eB+5OcZmOZtML36lvj3LfS6X+cJ7nPKmZi+A6BZa4iIRGZ+gjmxf5l26pRSlZOO2OkTgqOGiPjD\nppu+A5Hlf+CZ+A6Sk417y0WY+PMxw68qVjoBSfgbWfCLDYCSZ5SvsPaUGzTFmfw5xpgCRx3MtXfi\nnDTgSH5FVc3o+1PRJDMDsrOQpQsxMbGYzt0rukpBZO8e2LQW2bwh0AkF6NbH37kDMMMux5x5Ae4t\ngemAzv9eg7QUZNN6ZOnvQfnFAGjbCf5aC63a49x8P6ZBw6DD7lfTkM/fg+4nYLr2wvQdSFyz5mXa\nnkSkyCmvkrAd972XYfVSzBUjcXwP2CQnG4R86RUkcRfui49jmraAHici338Om9YB4Ix6FtO8jT1v\nyXxo2T5oOr3s/Bt37B2BaaE+5sIrcM4ZEXyfTetxH787UBAegfPg00HBrfznpqfh3nZJ4HoXXY05\nOR4iovJ9dogIMvU5ZO4P9tyhl9rp9oeZGSIisGaZnaLsG+X1H/N6ITMd9+4rMX1Owbn2ziKvVZb0\n/UmFkranopVp8JS0tDSeeeYZvF4vERER3Hnnnbz66qts376dnj17Mny4/XCaNGlSscqKoh07FUru\nvB+RN56xO+074/mPzRfnHTUSdmzF9B2Ac03+D0rJzPQtSreD3P7olkMuxTk/8CFfUHvK26H0vGrT\nL0jyAdy7LrfXuOo2GyWzZuWMpKcqjr4/VR+SnY38+CWybqVd93dwv03F8Pl7wSc2aGhH5wAaNoXd\neT4Du/XBNG5mOziHcMa8BHVjMJFRuD9+hbw/2Zbf8zimU1egcrQncb12FK1jNzy3PgCA98GbbITi\nE/tDl16Y409FZn/r/x2CtOmIOf0cnH5nFO9+IjaYy/NjYOc2nMcnY+Ia5zvP+8jt8HeewDJtOtpp\nnDVr4j56BzRoiOnQBdm+2Y4O9u4Hu3dCnmA0zoSp4Lq4k5+CfYmB/4/d+sCBJBscq0tPnJvut3kQ\nf/kWaoZj+g1EPnsXaoZDnbrInO8h4W+o1wDnipE2cNCSBfmD0dz/ZKFrQctDZWhPqvrQ9lS0Mu3Y\nzZw5kyZNmnDcccfx6quv0rFjR1asWMGtt97KlClTGDx4MFu3buWPP/44bFmTJk2KvJd27FQoievF\nvfsKSEmG7ifgGWlHzbz3X+f/EM7tfPlfk5ONe7N9COG88CGkp9l1NGADPzRvg3PNHZimLYPak6xf\nZaf+NGyCfP0h5tIbcQYMDlw3LRU2rrHhp0sQYlodPfT9qfqTfYm4/7nGv++Mfh733UmwfpUt6NQN\nZ/DFtmPhS/Hg/vKtTSFw7sXIx1OR33/xv96c/0/ky/ftdu+TMdfd7X8gVVnakzv1eeTP33Buvt92\ngpIPFHquOWc4RNeBvzdjThmE6dilTOokrheS9kJ2NrJ2OfLOS4XX6fxLcIZcaqfOvjCm0PMA+//v\nrmeuSloAACAASURBVDHg9eI+/yisXlq6CsY2gsRdUKceNG6GaX8szrDLS3etEKks7UlVD9qeilZu\n6Q4mTJhAeno65557Lr169WL+/Pmkp6ezadMmevTocdiyAQOCp57NmjWLWbNsDqFx48aRdcg0ilAL\nCwsjJ+9Cd1XtpX78FinvvEyNLj2JGfsiAGnffkLyK+MBCD/+FOreM8Y/gpb+0zccfM5+eNe++T4Q\nSH45ONR6ja69iBnzgr89ZW/ewL47r/AfD2vTgbr3PU5Y42bl8SuqakLfn44ubspBnOg6uOmppH3y\nDmkzPqbefydQ85huRb4u7asPSX7tmaCyyHNHUOf6u4LKKkt7Sv9xBgefHxtUFnHqmWT8Ogt8X0lM\nRCRx78zEeComFEDG3B9Invoi7p4ETFQ0de8YhYmMIqxFaxxfBEkRwZuwHU/jZhx85hEyZn/nf33c\nW9/iTdxFWOv2/gd34vVy4JlHkLRUJD0NExWFUzeGzN/nUOuiq6jZrReZ834irGVbwk/qT/p3n5O1\ncglRQ/9JzU5d8e5LxKlbr8L+JoeqLO1JVQ/anopWs2bNYp13RB27devWMW3aNOLi4jjnnHNo3bo1\nS5cuZdOmTezcubNYZRdcUHRodx2xU6HmTwRetz6e8VP95e4PXyLTXgXAuWuMf71Obr47v9Yd7LTN\n7icgC+eAMVCvAZ4nXyfi+89I/fYTOLgf8K2pGDBYF7GrUtH3J1USsnsH7kM3gwjOY6/kS+JeWdqT\nHEzCvf96CA/HDL4YmTEd585HIaoWRNdFfvzSjjY2LHpGT7nUNTUFsjILDVLjP08EMtLB8UBONqZW\ndJHnVweVpT2p6kHbU9HKPCpmSkoKr7/+OnfffTdfffWVf2QtIyMD13WJiIgoVplS5c634J469YKK\nTYs25D7lkO2bMZ272zxBMw8Jnb55vZ0Wdd1dmGvuQL54H5n5CZKTTeqHrwfOa9YK57xLUEqp8mAa\nNsUzOf/6u8rG1Knvj2BqatdFzhgSNB3dHBLcpCKZWtFQjE6aMQYio+xOEVEylVKqLJUqaVdOTg4T\nJ07k0ksvJS4ujrZt27JmzRoAtmzZQsOGDYtdplR5M+HhOHc+gvPvh4PLO3bFeX4aNG6OrPgT+H/2\nzjw+ivL+459nNvd9bMIpKCitiiAiVtRW/Em1WitVvGqtttajVqpFrdVWCwreVqyKWBVb6n2hUK8q\nokjlqBciR+S+QhLInd1NdjfzPL8/njme2SPZTXazSfi+X6+8sjM7O/PM7jPP83xvSIucgXbbQ0Ca\nzNqmXXgFmOYCS0uXtY84t+LwrOPPvxwEQRBEOCwzCyy/UL6mGGOCIIiE0CWL3dKlS7Ft2zYsXLgQ\nCxcuxKRJk7B8+XI0NDRgzZo1uOuuuwAAM2bMiGkfQfQ07IjIdZxYVg7YqNEQny6BCAatjHTaTXeD\nDT8U2uOvhS9CxkwAu+S3EC/+HWkjvgN+411AYz1YaVmyb4MgCIIgCIIgACSwjp3H48HatWtxxBFH\noKioKK59HUExdkRPw1d+BPHMHHtHZjZcj70c/QMGwuuBe8hQ1DU2JrF1xIEEjU9EIqH+RCQS6k9E\nIqH+1DFJj7ELJS8vDyeccEKX9hFEb4KN/C4c2g5/a2yfy82z0ooTBEEQBEEQRE/SpRg7gujPsPJB\nYGdeILNfAtDunJviFhEEQRAEQRBEx5B5gSAioJ1zCXDOJaluBkEQBEEQBEHEBFnsCIIgCIIgCIIg\n+jgk2BEEQRAEQRAEQfRxSLAjCIIgCIIgCILo4ySs3AFBEARBEARBEASRGg54i90tt9yS6iYQ/Qjq\nT0Qiof5EJBLqT0Qiof5EJBLqT4nhgBfsCIIgCIIgCIIg+jok2BEEQRAEQRAEQfRxXDNnzpyZ6kak\nmhEjRqS6CUQ/gvoTkUioPxGJhPoTkUioPxGJhPpT96HkKQRBEARBEARBEH0ccsUkCIIgCIIgCILo\n45BgRxAEQRAHMB6PB2vXrkVzc3Oqm0IQBEF0g37riunz+fDwww9D13VkZWVh+vTpeOqpp1BZWYlx\n48Zh6tSpAIB58+Y59r3//vtYsWIFAMDr9eKwww7DVVddlcpbIXoBXe1P+/btw/z589Ha2opDDz0U\nl156aYrvhOgNxNqfGhsb8dBDD+HOO++0PhtpH0F0tU81NDTgwQcfxPjx4/Hpp59ixowZKCgoSOWt\nEL2ArvYnXdcxbdo0DBgwAABw+eWXY9iwYSm7D6J30NX+RGvy+Om3yVOWLl2K8ePH44ILLsCGDRvg\n8/lQU1ODW265BStWrMCgQYOwYcMGVFZWOvYdffTRmDRpEiZNmoQ9e/bglFNOQUlJSapvh0gxXe1P\nL7zwAn7605/ivPPOw9KlS1FQUIDy8vJU3w6RYmLpT4wxPProo/D5fPjhD38IQFpWQvcRBND1PrV5\n82Yce+yxOOmkk1BTU4OMjAwMHDgwxXdDpJqu9qcdO3aAMYbrrrsOkyZNQmFhYYrvhOgNdLU/jRw5\nktbkcdJvXTFPP/10jBkzBgDQ3NyM5cuXY+LEiQCA0aNHo6KiAuvXrw/bZ1JfX4/GxkaMHDmy5xtP\n9Dq62p+qqqqsLE+FhYXw+XypuQGiVxFLf9I0DdOnT0d2drb1uUj7CALoep8aM2YMRo0ahQ0bNmDr\n1q0YNWpUStpP9C662p82b96Mzz77DLfffjseeeQR6LqekvYTvYuu9icTWpPHTr8V7Ew2bdoEr9eL\n0tJSS8rPzs5GU1MT/H5/2D6T9957D6eddlpK2kz0XuLtT8cffzxeffVVfP7551izZg2OOuqoVDaf\n6GV01J9ycnKQk5PjOD7SPoJQibdPAYAQAitWrIDL5YKm9ftlAREH8fankSNHYubMmZg1axZycnLw\n1VdfpaLZRC+lK+MTQGvyeOjXI7jH48EzzzyDa665BllZWQgEAgCAtrY2cM4j7gMAzjnWr1+PI488\nMmVtJ3ofXelPU6dOxbhx47B06VKcfPLJyMrKSuUtEL2IzvoTQcRLV/sUYwxXXHEFRo0ahS+//LKn\nmkv0crrSn4YPH47i4mIAwJAhQ1BVVdVj7SV6N10dn2hNHh/9VrBrb2/HnDlzcPHFF6OsrAwjRoyw\nXC137tyJ8vLyiPsAoKKiAocddhgYYylrP9G76E5/Ovjgg1FbW4uzzjorZe0nehex9CeCiIeu9qk3\n33wTy5YtAyATHJBFmAC63p8effRR7NixA5xz/O9//8Pw4cN7stlEL6U7cx6tyeMjLdUNSBZLly7F\ntm3bsHDhQixcuBCTJk3C8uXL0dDQgDVr1uCuu+4CAMyYMSNs35o1a3D44YensvlEL6M7/Wnx4sU4\n66yzkJmZmcpbIHoRsfYngoiVrvapyZMnY86cOVi6dCkOOuggjB07todbTvRGutqfzjvvPDzyyCMQ\nQuDYY4+14qqIA5vuzHm0Jo+PflvuIBJmrZ4jjjgCRUVFUfcRRCxQfyISCfUdItFQnyISCfUnIpFQ\nf0oOB5RgRxAEQRAEQRAE0R/ptzF2BEEQBEEQBEEQBwok2BEEQRAEQRAEQfRxSLAjCIIgCIIgCILo\n45BgRxAEQRAEQRAE0cchwY4gCIIgCIIgCKKPQ4IdQRAEQRAEQRBEH4cEO4IgCIIgCIIgiD5OWqob\n0Bl79+5N6vndbjdqa2uTeg3iwIH6E5FIqD8RiYT6E5FIqD8RiYT6U8cMHjw4puPIYkcQBEEQBEEQ\nBNHHIcGOIAiCIAiCIAiij0OCHUEQBEEQBBER8eVK6FeeDbGvKtVNIQiiE0iwIwiCIAiCICLC//uB\nfFG1O7UNIQiiU0iwIwiCIAiCICLT6pP/s3NS2w6CIDoloYKdx+PB2rVr0dzcnMjTEgRBEARBEKmg\n1Sv/Z2Wnth0EQXRKwsodNDQ04MEHH8T48eOxYMECzJgxA88//zwqKysxbtw4TJ06FQAwb968sH0E\nQRAEQRBEL8S02IGltBkEQXROwix2u3fvxmWXXYZzzz0XY8eOxbp168A5x+zZs9HQ0ICqqiqsXr06\nbB9BEARBEATRS2kzBTuR0mYQBNE5CbPYjRkzBgCwYcMGbN26FR6PBxMnTgQAjB49GhUVFdi+fXvY\nvkGDBjnOs2TJEixZsgQAcO+998LtdieqiRFJS0tL+jWIAwfqT0Qiof5EJBLqT0RXqDEsdkWFRUhX\n+g/1JyKRUH9KDAkT7ABACIEVK1bA5XIBAEpKSgAA2dnZqK6uht/vD9sXyuTJkzF58mRrO9lV6KnS\nPZFIqD8RiYT6E5FIqD8RXUJIS11jYyOY0n8S3Z9Emw9gGlhmVsLOSfQdaHzqmMGDB8d0XEKTpzDG\ncMUVV2DUqFHYvHkzAoEAAKCtrQ2cc2RlZYXtIwiCIAiCIHo7yXXF5L+7CPzGS5N6DYLo7yRMsHvz\nzTexbNkyAIDP58OUKVNQUVEBANi5cyfKy8sxYsSIsH0EQRAEQRBEL0f0QIydvy351yCIfkzCBLvJ\nkyfjk08+wYwZM8A5x3HHHYfly5djwYIFWLlyJY455hhMmDAhbB9BEARBEATRy6HcKQTR60lYjF1e\nXh5uv/12x74ZM2Zg7dq1mDJlCnJycqLuIwiCIAiCIHozJNkRRG8noclTQsnLy8MJJ5zQ6T6CIAiC\nIAiCIAii6yQ0eQoRGcE5BNdT3QyCIAiCIIiYEWpcXU/E2BEE0S1IsOsB+C1XgP/+klQ3gyAIgiAI\nInZ0RSlNgh1B9HqS6opJGDRQXQ6CIAiCIPoYenuqW0AQRByQxY4gCIIgCIIIRxXseshixxf+q0eu\nQxD9ERLsCIIgCIIgiHDae95iJ959rcevSRD9BRLsCIIgCIIgiHAcgl3yLHaUYI4gEgMJdgRBEARB\nEEQ4DlfMJF4nBZZBguiPkGBHEARBEARBhNNTMXYk2BFEQiDBjiAIgiAIgghHLXeQTJMdZd8kiIRA\ngh1BEARBEAQRTk9Z0shiRxAJgQQ7giAIgiAIIpz2oP06qTF2wc6PIQiiU0iwIwiCIAiCIMLpMVdM\nZ1ZMUbkzedciiH4MCXYEcYAhuA6hU2ppgiAIohN6KnlKSIwdn/m75F2LIPoxJNgRxAEGv+0a8Osu\nTHUzCIIgiN5OO2XFJIi+RFqqG0AQRA+zvzrVLSAIgiD6Aj2VrZJi7AgiIZDFjiAIgiAIgginpwQ7\nKndAEAmBBDuCIAiCIAgiDBEMKBvkikkQvR0S7AiCIAiCIIhwWn3KBhUoJ4jeTsJi7Hw+Hx5++GHo\nuo6srCxMnz4dTz31FCorKzFu3DhMnToVADBv3rywfQRBEARBEEQvw+e1Xye1jh0JdgSRCBJmsVu+\nfDnOOuss3H777SgqKsKnn34Kzjlmz56NhoYGVFVVYfXq1WH7CIIgCIIgiF5IW2uPXEaQYEcQCSFh\nFrvTTz/det3c3Izly5fjzDPPBACMHj0aFRUV2L59OyZOnOjYN2jQIMd5lixZgiVLlgAA7r33Xrjd\n7kQ1MSJpaWlJv0aN8T/Z1yFST0/0p+5C/bHv0Bf6E9F3oP5ExEtLehpMZ8yCgnxkKv0nkf2pNTsL\nzSH7qK8eWND4lBgSXu5g06ZN8Hq9KCsrQ0lJCQAgOzsb1dXV8Pv9YftCmTx5MiZPnmxt19bWJrqJ\nDtxud9KvYdJT1yFSR0/2p+7SV9p5INOX+hPR+6H+RMQL99qumM1NTWBK/0lkf+KNDWH7qK8eWND4\n1DGDBw+O6biEJk/xeDx45plncM011yArKwuBgMym1NbWBs55xH0EQfQcQtdT3QSCIAiir6Cu05IZ\nY8dpbiKIRJAwwa69vR1z5szBxRdfjLKyMowYMQIVFRUAgJ07d6K8vDziPoIgepCgP9UtIAiCIPoK\nDgV8MrNihiv6+T8fSd71CKKfkjDBbunSpdi2bRsWLlyImTNnQgiB5cuXY8GCBVi5ciWOOeYYTJgw\nIWwfQRA9SCDQ+TEEQRAEAQCihzyrDIsdO/FU+9KfLumZaxNEPyJhMXannXYaTjvtNMe+Y489FmvX\nrsWUKVOQk5MDAJgxY0bYvgMF0R4ES0tPdTOIA5kgCXYEQRBEjKguksksUG5aBrNzk3cNgjgASHjy\nFJW8vDyccMIJne47YGhrBfJIsCNSiGKxE0KAMZbCxhAEQRC9mp6OsdNcSbwIQfR/Epo8heiEVl/n\nxxBEMlFj7JKpfSUIgiD6PnpPxdgZgp2LlqUE0R3oCUoyQtV29VChT4KISjCobJBgRxAEQXSAGmPX\nE66YIRY7QQpIgogLEuySjd5uvybBjkg1AdVil7pmEARBEL0f0VNlCKK5YlJZLIKICxLskk27KtiR\nKyaRYtTkKaQJJQiCIDqiJ8sdMA1whQh2PZWVkyD6CSTYJZt22/VNGDF2orEegoQ8IhWQKyZBEAQR\nKz2VPEXoMr7OPSD69QmC6BQS7JKNupA2XDH5H34JPvO6FDWIOJARiqKBLHbJRwjhjLMlCILoS3AO\naMZSMZlzhs4BzQV27ElgP/mZvZ/mKYKICxLsko3q+qZa6er29XxbCEKN+aQJM+nwB/8Mfu15qW4G\nQRBE1+A64DIrYyVvzhC7tgIBP5jLBe1sRbAjxRhBxEVS69gRAOpq7NetlDyFSDG6Wmw2dc04YNi0\nLtUtIAiC6BJix2Zg/Vc9c7GKtVEaQYIdQcQDWeySjKjZa29QXB2RatRkPiTZ9Rg9llmOIAgiQYiN\nIcJWKqYMstgRRFyQYJdsavYCmVlAXn7IopogUoBOMXYpIUjPPkEQfYz8Avl/5HeNHUmeM1wRnMho\nniKIuCDBLsmImr3AgMEyjW8SXAoE55ScgYgdstilBlWgJgiC6AsYngbaWRfJ7SQJWaZHAztDiUc+\nZJTRBlrfEEQ8kGCXbGoqwQYMkVmlkjAo8mvPB7/7poSfl+inqIIdyXVJRbQ02xs6uWISBJF4xNrP\nIPZsT87JdUOoSpOWtKQZz8z8A7m51i524mT5gmLsCCIuSLBLIqI9CNTuMyx2LDmjYnsQ2Lkl8ecl\n+g2iZq9dN9GRFZMmzGTC5862N3RyxSQIIvHwR2eB33F99PfnzwH/bHkXT24opCK5SCYSn0f+z86z\n95klFshiRxBxQYJdMtlfIxfPpismDVBEDyO4Dn7bb8Dn3Sd3tCoJfMhil1zUkiZksSMIIgWIVR9B\nPPlA1z5sjlumkJWsScPnBQAwxWIHxoxL0kRFEPFAgl0yqakEAOmKmSyLHUF0REOd/L+1AgAg6vcr\nb1J/TCq5+fZrstgRBJFgOouvF91dc5gWO8MVM2lrGLLYEUTCIMEuiVilDspNV0waoIgeZn+1/F/i\nlv/blFqKpGhILrnKIoUsdgRBJBp/W8fvK2sOYVjF4sIct1wu4yTJtdjBYbEzlqe0biKIuCDBLpnU\nVAL5hWC5eUlLnmJCmTGJSAhTsCs2BDu1n5Bcl1xyyGJHEEQSURV1kVAVSs2N8Z/fnC+SHGMnOrTY\nOScqvmQRxNrPktoegujLkGCXRETNXqB8kNxgDOC8+64R0aDi53Ehdm2F8LakuhnJp2o3AIAVFMlt\nh+WIJLtkwvJUwY4sdgRBJBaxZWPHB6jjTlcsX1yXaxfTerZnB/g7r8Z/ns6IaLEzY+yc7RYvzwd/\ndFbi20AQ/YSECnaNjY34y1/+Ym3PmzcPt912G15//fUO9/VH+PNPAJvWgVmCnWGxS5Zg5/VEb8vq\nZdCnXQAR8Cfn2n0M0R4EnzUd/PF7Ut2UpCM2rZf/V30E0VBnx0wA5OKSbLKy7dftZLEjCBPh80C/\n+yaI6j2pbkqfRjx5f8cHqOM978LaQ9cBzWVf773XId54NvEeQj6vtNBl2mMmM18rLqRJU4wTRD8i\nYYKdx+PB3Llz4fdL4WH16tXgnGP27NloaGhAVVVVxH39FfHxO/JFmSHYaUZWzGS5TLZG958Xi1+U\nvviVu5Jz7b7G/hr530hu069pabJf79pGrpg9iboIIYsdQViIb74Atm+CWPRCqpvSv3FY7LowBnEd\ncGm29Uzdn0h8HiAnF0y9ztCDAQBi1zZ7Xyt5JhFEZyTMcVrTNEyfPh333y81SOvXr8fEiRMBAKNH\nj0ZFRQW2b98etm/QoEGO8yxZsgRLliwBANx7771wu92JamJE0tLSknINQ3RA3tBhyHG7UZuWhrSM\ndBSWlsBMgp6I65rXKUxzISPK+WrT06ADKMzPi3rMgUSgtgoNAFz5hQn/7ZPVn7pCe3Ul6pQsmPl5\nOfBqDKbtqKS4GK6S3tHW/khzVibMCJjCvNwuPXu9qT8RfZ/e0p/8AwehEUC6HkRxL2hPX6VGeR3p\nd9U1oNZ4XVRYiPQ4v+uWjAy0amkoLilBnXqt4mKwzCy4NA2lJSVgWtdsBIGKb5B+8KFo5u0I5hU4\n7kGUlmJ/QREy91Wi0NjfXtVmtaM39GMisfSW8amvkzDBLicnx7Ht9/tRUlICAMjOzkZ1dXXEfaFM\nnjwZkydPtrZra2vDjkkkbrc7qdfwQoOvthY659A9HtTusxfaibxu075qsCjn0w0ralN9fdRjDiRE\ntcxWqrvSEv7bJ7s/xYoQAvya8x37mp77u8OCV19fB0bemEmDe23tclefvd7Sn4j+QW/pT6JFxjcH\nPC29oj39gUjfo6iyXV0b6+vB8uP7rnlLC0SaCw0NDc5r7dsHlp0D7W8zEVy/Bq4n34y7vSLgB7/1\nauCQUbI0TGZ22D2IoYeg7dt1CBr7xe6d8o30DOo3/ZDeMj71VgYPHhzTcUlLnpKVlYVAIAAAaGtr\nA+c84r5+z5Hj5P/6/cA3n0Os/ihhp1b9zYW/g/g5M76HYqoAAKLVsKNkZvX8tXdtg37n9RDdTHYj\nvC0QwUD0AyK5/u3ZATQpEzS5YiYX9XkjV0yCsDHWATQGJQ4RDIbt488+pmx0Yf7X2wFXOsJ+KCPL\nb3Ddl11fV5gx/9s3yVCSnNywQ9jQ4YAinIp9RgmpopKuXZMgDgCSJtiNGDECFRWyKPLOnTtRXl4e\ncV9/RBW4WEamfGH4hosVSxN3IWWgFi8/Hf04M9U6LS4l3mb5Pzun4+OSAH/tH8Du7cCWiu6d5/c/\nB3/o9ugHxJJenwLRk4u6kKJyBwRhYSmluqFsFNWVEJ2l+z+QiDTG7Nhiv+6KYBcMyuLkgRAlYiJi\n7NoVQbTVF3k+zsh03tdWY94cOLT71yeIfkrSBLsJEyZg+fLlWLBgAVauXIljjjkm4r5+SUeTVSKD\nf9XBVU2SEYpZI+ZAsJDGQp10h2X5hT1/bVOrmp7R/XN1lOramDTZTy+xgtBDER+8CdFY3/12EJFR\nLeok2BGEjSnYdWNO4rdfA/7AnxLUoD6KWcYGCBO2hM9rf89A14To9iCQnu48DwDoISUIupL1V7Uw\n+tvAMiJ40BjZxM0snGLbt/FfhyAOMBIu2M2cOROAjLmbMWMGDjvsMMyYMQM5OTkR9/VL9A4G0OaG\n6O/FfZ0YtWbmcYnOZNVXqTPS16TCYmVOkC5Xx8d1F3Oizc2HdssDEQ8RSxaDP/VgcttxIKNa1J98\nAIKeP6IXI/bsgNjbQ5mTuynYWV4xu7YmqEF9lGDArjEXKmx9tUq+KDU8o7pQ7kC0t8vi5FkhazW9\nHUJZf/Bbr4z73A5hMeAHMjPDjzHnSbOfmEXWyduEIKKS1ALleXl5OOGEE1BUVNThvv6E2LMDYs1q\nAAA775fhB3gSWBQ7hoWio3YdWewAAMLMFJmK78OczNrD4yFiJSYBwRTs0tLAIk2YJuTKlDwEd6YJ\nb6Xvmui98DuuA58xrWcuZrr2ebs4HyrjZ4fx5f0YEfBLD6BiI94sdF5okUKQdvHVxge6aLFLSwcb\nNBTaTXfbaxquA55m+7jGuogf75AQi13EmHcz26bZdvN376P5AoS3BaK2pvMDCaIbJFWwO9AQ33wB\nfsd1dtFQLclWGVND53I5iyGrmNYpICUWO6Hr4Ks+SnxB0+5guGKmZHJIgGCHYAxuL7px/rROEt8m\n23KYYoTXA/3Ks8E/+2/PX5xz6cZkEjwwF6AHGkLXIXZvT3Uz4kKsWWW/7olYbPNZ6Kpgp8Z8bete\nvHKfxbReFZXK/6G/m9cjx3+z0HdX5uD2oDWHsO+MljFvAMTH79rX7yqhFrtIrpjmGsq8N1MY7KMW\nO37n9V2zbvYj+KvPQGz4KtXN6NeQYJdARMXXzh0d1XbJSECMlSmopWVEHbRFxVr7dUcuoklCvP8G\nxPw5EJ8t7/FrR0K0B4EmI64sJRY7Y2LqjmDX3kE2TOsYKfyxtPSOj3MlrOJJr4MvWQT++4sByHjC\nnm8AB9TvP0CC3YGAWPgv8Duvh6je0/nBvQT+yfv2Rk+02xTMuhKbBTiEAtFdAaOvEirYhSoqfV4g\nOzfc6tUJavI3BAPOePAGo+zAksXdF+xC58BIyVPMtvMQi10C5m6+ZBH0jhKQJYP6AzuVv+A6xPtv\ngs+Zkeqm9GtIsEsgomavc0dHFrv8BLiimlqs9PTo1rh9Sq3AVMT41FTK//62nr92JBrqbG1fCmPs\nIqWmjvccHWJOgJEEtzET7Ne9yKVF+NvAn5kD0dT9OFSxby/Ey/PtHYlMWhRzI4QzNqUPCXZ81ccQ\nm9aluhl9EivBQx8ROISuA998bm/v3pb8i5rjXzDQNW8OdQw8ULM9G/2LFUex2JmJT0KFow4QnINf\nNQX8jWfljqYGMDVBi2IxE1VGPOYho4CSsvjbHzoHRih3YK2huC5DEMx7TMDcLV6eD2z82inIJhE1\ng+uB6j6c0FAkIiok2CWS6krAPcDednXw9RbEJ9iJSBYe03KTlh49YUur136dAguVNZhF0MYJnxd8\n+fs9NrACcAws0WLVBOfgLz4JUbkz8dc3F/fdyZIYRSgUPi/4S09BtPrsYzLC4+vYhJPs1+WDut6O\nBCNWfAix8iOId17t/skaQrJ9psB6IjgHsrKhXfcXuaO1Ffz9NzuuP9hLEPMfsjIOCk8z9PtvEEKh\nkgAAIABJREFUgVDduonomGGVfcVbbN0Xzu1dPSHYKQvbrii51PmwFymnehJhJmIrihJjZ8TH2Ra7\nGDqkkUFbLFkkt1uaHGsVduJk+/qG4owNHNq1WO2QcZBFFOwUoVQNQUjkb25mDU82AUW57W2Oflwv\nQbS1JlS5J/ZXg994qdxIQampAwkS7BKEaA8C+6uAIcPtnR1Z7NI7cZFTz/31Z+DXTIXYY8dtiOpK\n8D//xj6X4BEFJNHqs90+U+F6aCaM8HoccRwApHXmX48BPZWJDXAOrtG+j9pqiKVvgc+7N/HXNyez\nbrjFig1rIu9f9DzEh/+G+HKFLUBGEOzslSfiVjAklRZjsos0wceLp4PyHz2FmTzFiB0RK5dCvPoM\nxKIXUtyw+BCrlwGbN0D8Z2Gqm9I3YH1LshMNTvcw0ROCnRoj15XYU9UCf4Bb7FBoCHZhJQiC0mPD\n7I+xzP9mQpSMTLmeCPgdSU3Y0IOBYSOdnykuBdp8cStowxRc2RHGfVM5znVnCMKm9RAb1oC/9TL4\nE/fFdd0wupFATDQ3xvy8iHdeszc8fUCw++cj4A/8KWElkcTnn9obOXndO9c3n6cmbr6PQIJdothf\nA3AONniYva8jwS6O1MNinXSTEZvWK9dTXCzNOJ5IA3ebD8jJN95PwQTYZhRmf34e+Ny7IdQBzazD\n1pOZGdVrRZvoTA2ymtEw0XTjtxDPPR75DbOWIWMdC3bqffWmRZHZN3Lzu32qeF1dhRDgn/23ey6y\noei6TE4T8huI/ywE76XCndB16KEKDbOPJDsZFNFjiF1brezNppClPfQc2PdPA3ZvT74Xhbqo74pb\nmlexsiRxXhNfroA+YxpEQxeyPiab5kYgJ8/OehxmsWuP2xXTGoNdadKrRIjwmquhJSayc+S543U1\nN62uZj3ZiFkxzeQpPMyyy+f8RSozv/g07GNxuTqGFl+PAz5jGvis38d0rPjw3/ZGH3BJNF2yxavP\nJOaE6tqrm94f/JE77SSFRBgk2CUK09XLYbHr6OuNY+I0s0WpcWq6MsgZD4xY8WH4Z1t9QK6hHUng\nIl7oOvjLT0P/28yODwyNbVLbYGZE66i4egIRXAd/bLbcSI+ecMYagOKwqsZ0fXWx1N36TZHflP99\nXvs+Q4QK7bY5zmv3psLZZn9IhJtGvIu99V9CPHk/xL9f7P61TRrrgIJi+zdQFiZi6b+jfCjFtDQC\nX65w7jO/y36caCexGIqTXpy5j8+aDj73LrlhCllZ2dIa4/MAZkmYJOGw1nThWkJ1n0uiJwpfshjY\nu8uRhKy3IJoapceFFlLrzcR0xWSxJ08RXxjPflODLXh1loDLjCOON445VIkWKYOzpljsOnBhV+dF\nvuJD8GnnQ1RXxtiObsS7xWh5E1//z7ntaYbYtB6ih9Y+XcLoV+J/n3T7VGJrBcSHi7t9ni5f3+eB\nPmu6w+utP0OCXYIwBxGHxU5JJa/d+gC06XcqH4hn0jeOZUxaFhb+C2LPDvttYwAW/3os/KOtXttV\nI4HJG8TCBTIz1rovOz4wNDbQbKty/6KnkkqocVdZ2dEnOnPREKqp7C6qZrCrWuaQLHJqnKC1WFIV\nAIZQwX55PXDEOLDhI52/SS+y2FnW3G4u1PhTD0L842/OnYqAy59/AnzpW85r1xoaxAQlvBBtPqBy\nl4w/MVyhhZraPVJq795ApMQ1Zn/pZeUa+NuvgL/2z1Q3IxzDIi4a62Ie23qyHIzweZ07AgHZ5rQ0\nsGEj5L5ku2MGA5YbuKjaHf/n1WcpmZ4opjJj396Oj0sFzYZg57ITjDgIjbEL6WOiucGKmxWcQ7/6\np3JONzFj2kIVnAcd4tw2FXE7NsXXfsO1kp15vtx2Dww/RhVaO8qgqsyt4suV8kWsIR6J9NKIQlgf\n9zSDP3Ar+IN/Tvq1u4yyfhVdzV5rwO+9OSyBXkz1eBOEWPsZsGur0x22H0OCXaLYt1cOsrm27zBT\nLHZsxHeAw8fax8cj2JkPleYCamsg3n3NGafTkabM67GzZrUlLjOgUAS6DhcloQsbK8ZMeai7kPpf\nn34J9E6K6YpWH/jL860ELmKx8p1lZYe5w4q2VvB/vwTRbGjRtn0L/Y7r4m5b1PZ8tdLe6KpAFfp9\ntigaQ7MfqIseoz9qJ54K1/Q7wq/dmyx2pntKN4XNiBrGYMBSJoiP34F48Un7eCEgnp8nNyK5A3UF\nr0d+t0OGAaarlGplyOqdgh3/2x2ObcG55fZmCb+9BPHmc7067k/MnwM+5y/OfVyH+HKlU7G1fRP4\n1T+F2Noz9disBAYmQT+QngHGGDDkYIBpyY+zCwSAgUMBAOLZuRDxpoFXniXx8nzo99+SyNbZmIvR\n0IzXvYHmBrDCYtsiF5YVs11awYx1iKPP+dvAb7wM/JYr5I5AW7hCzVTkhFjstIucddiYYbHjc++O\nr/2GQMVO/hFcTy2OIXlKBy6TapK4WGNczeN6QrEcao00FYg9mV8gXtQat8mICeyGC2zcmONLsRti\n/Vcyv0Mv9qjoLiTYJQjhaZa+4mocSogGiqmxTarrwGf/7djVwxTsdD2yNSNEMOKrl8m/t1+Rbo4H\nHSIFmUSmfFcfiigxcoJzeX2leLr4cqXc7xDsuiBceJo7HBSFEOB/vQ1iySKZtELXna6qOXlhQo34\n8N8Qi19wZmXcsyNhqYnF/IfsjWgZOYXoOM4rtGyEamExBDpRZWeAZJEK1zsEu9iEKFG5K/luDObk\nkQwrohDRFQjqpBUx2UwXMBch6Rl2gWB14R4pUUBvINQ1qNVrL7q78bsIrydpbkc8EVlUk4UZRwxD\nqHv3dfB59zgSCYilbwOQWm39zuuTmgpdcB7+HAQDllWZZWYCA4ckv+RBU70zgYIaMx4LXo8z1GHz\nhsS0KxRDYBD7qpJz/u7g80rFnelZEgxABPzgCxdIjwHTYmcKZoYAI4QA/3tIfFKkOdgbxXNFccnO\nGHMskK3M7/H03aCS1TsKTLVGdqQAdqxtTFfoTq5v9p8EZCnuVEhwOe9RfPKfbl8zUQifF8IbITOo\n6nqfjGRkXRSou5RV2oyRzckFf3iGzL791INdun5fgAS7ROHzyEFWnWyGHhzTR8WT94P/9bboBxjx\ndGLhgrDBjU35OXDo4c7zPf1X+ffmc2DH/UAGxGflOLVa3UCs/QxQXQuiCYxej0woM+XnVp0b8caz\nECs/csYIdqdYd7Q2Lv8PsHOL3NDbwyeu/IJwIclc1Ie63STQ0mkRraD8ksXgv50aeaAF7Kye5mSr\nCnamgGL8NtoNsyKfQ4/fFZPPnAZ+x/UxHSuCAYiWLmj4LFfMJLloBPyRrctqVsBEpdE2tJEsPQMs\nkhUwksDdG2lssGPuOrHuirZW6FeeDb78/bD3+N03gd/wC/BPpXJF7N4O/t7rXdaaOqwP778p3R5D\nXQyjfXZ/NfR7/pCwbG8RGufcDPgh/H6ZYe7N5+ROZaEk1GQUu7c7FFZif3VC3DT5C38H//AtBL5c\n6dgvdF321XRFoVHsTmoNPqHrwP5qMNWlL1J8VUfnqK1xlhZKFuY43NALC0sH2qRLd55MNiUqd0A8\n/wTEu69DfPiWtIilpdsCtCmk/vcDR91CAJEFO8NNM0w5aApb2bkomvGws1ZnaxylA4JB6f7bUZIy\nplrsQtYJgw5Srqta7MwXnYwtphI+EeVnOntGa2uMaxr3k8TYOuHz2rU0Ozu2vhb8+p+B//7i8DfV\ne2ruPYIdOlhbiLr9EOa6T91fWx12TfHZ8q5dvw9Agl2i8LRILbxivmaujrJixjFZq/7jZiYzA+2s\nC6FddJXcGH6o4z125gVgV9wIlpEJZOdAtCYm+yR/NERgiCYwNsigeFbihvbrG+z9Pg/Ev+ba2zEK\nduLLlRAbvnJm1ozG9s32a78/bFHKsnLCLY3RknYkwFVDhGqUowhUwlwUb90Y8X2zLezcX8jjt0kr\nkBDCFozMjFOhsRDWOZT+lARXTP7An8BvuCSuz4g2n/09t3R9USk6EsIDgcjWZdUNLFTY7yqqxQ4I\nS6TEDDe0aIhgACJeK0YXEFV7oD9wq1UTi034vvOAesX9sjMlgKEVDa1DKDi3lSXbv5UWg1fmQ7y+\noEuaa8E5xMJ/2Tu4Dv6HX4HP/F1Mn+d/ugrY9i3ER2/Hfe2YUGo/seNPAf/TVeA3/sJhvXN4doQu\nLA2hSlTvAf/TVRDvdj8uRHz0NsRLT6Jl/sPON9qD8vqqVSY9PSnKNgvzfjOzgJHftdthtrU9CH3u\n3RA7t0b4sEF1pXNhnwSEEPbclqhxIUEIzuV4lpFpZREWL8+3vVLS0oD2IFhaupzXGAO8XoiGOqv+\nnAPj+2eX/BbsZ3I9ITZ+Ld8bHlLewOy7aWky3ESdN+Nxr2sPdh7HrlrsQuveHXWsvaEql80Y15BQ\nC75iKfTfXWjHi5kuql1wCRSeZuhXnm3v6Ezp9f4b8pI3hburxpzkJda2vfEs+D1/6NTKLIToOONl\nqxcwYm677W1hPOfswl8DY4+T+7rqmbDfvq9QxSC//Rrw2TeEfkKOF0C3s3H2FUiwSwCiPQjUVIIN\nPqjTlODa398ARo+3P6sslkRd5OxgQlmMWhpfwHLxYsNHyvi9tDRHsD479Lu2NiwnN2EWuzCUxbTw\n+yHMSdBMVlJUCowY5fiII0VxDK6Y4osV4PPuAZ8zA3x650KD+O8Hztehi9LMrPBFfjQXyES4aqz9\nDADAfmq0PYJgL3Zvt6xtUQuDGoMhK5OFxcVbL8v/bz4ffo/R3P3U+4nBYificOEVug5sjzOIHnAk\naxDvvu7o83FhakZNsrLtungBf0TrslCtE4kqvWEuVNMjlCLJzuk0xlb88xG5qE9gMXPR6guz/ojV\nH8uaUO++LrdDngFHUfLOLKlmbGeoBl5Z9Ihl74FfNQUwXM/FK09DxFs8ftu3EO/J9iK/0P5NY7Cq\niG/t50pU7ozvuvFSNlDee1NDuGCgCvqh458Z22TENIotsbkZxmL91KsrnZmbDfc9q9YpYAgFsSl8\nRDAYv0UxaD8b2oVmjJeyyKveA6xZBf73yPXJLItfkgU7+FuNkgEZgL+tRxPcdIr5HWZkGrH9ISVi\nGJN9zxS+TI+drRsBfyvYpDOcx5u/d1Y2WLEbAGQcfYkbzPC2sTCFLbMPq4JdPIlIgoHOM26qMXah\nz5C73H7dFi7YhYVavPh3Ob77jHHKPF8XinCLFUudO2J1Uy8tC9tlZadNEJYbdSfZZsXStyE+t2vB\nidB7aPWBlQ+Wr7uhbAUgPREGDoU2eQo0s+910ROKv/m8vWF4LIlgQJYQMuZLdR0sggFLoBNbnArz\nXlnGJAGQYJcIWprlg106oFPBjmkuOVhZqemVIPCP3pZuO+u+cH4oygPALr7a3tA0gHNnNsBMxYUi\nK7vDRavweSHq9sVmDQtFWSzzW68Av/5n8pymW0ZuPlhaOrTbpbZYvBKiMYxBO8yjaK1jqjtWW+Nw\nP9RmPS6/D3+oYBdFg9RNba0QwlqIWhnAIiySTeEPCB+AwtoSMpGLd15xHpeRGd1irGooY7HYqRqy\nDjLYiQ1rwH9zTufni/TZELc4sfKj2D8rhL3oCtG+ao+8BO0yw5IT8DuVEKbQok4Cqz6OvdEwrMiR\nJtBQi51KR6U2zPMalvn23XZcY4fWyM7aWbcf/LqLIJ5/AvpfrrUndCOOQpjCeHNIVkz13jpZvAhT\nqA51Pe1IS5qRCT4/zkB2VdgNXXR2Av/gTXsj2QkxdD26u4/6bPrbHMKW0HUIzsHNxDCs82lan/k7\n8Hv+ID/PudO9UyHt0MPBDjvS3hEMyj+ln7K02Cx2YtdW6Tb+4t87PdaB+mwY2WEdyiPT1Sra2FRX\nI98bOMTeF8N3FAtC16WiFrAEa5iZrnuT1c50yc/IlIJbWUhGybY22xUTkMotn8eyTrEfTrEUzILr\n1nfN0tJsN/F9e+17VzHXOOZ3rrpqtsemiBLt7RDL3uvcJdGqY6eHjX+sxBbshM8LUbNXWtHMkg3K\nOCFamuz1j9frzCb93w+gz74hrCRBh4SupWL1fIlUMibR/SrGpDBizSrnjtCMyK1eKYi6XN1yxRSN\ndbItpgLPVDh31dCgKroMF0vx0dsQb71k71fnrX3Vcr2dnRs2F4kQ1/T+Agl2iaBOLmhYfgHgiuEr\nZQxWLI9aqLLYDfHyfPC/3eFMVBFFIGNFxfaG5gKaGhwaGNXHnGV3bLHj1/8M/JYrwO+/tfP2mxiF\nRR2xLS1NchBeswowF+uGxYQNGwGM+E74eWJx+4nmsrE5XNsWcZFoLErZ8ZOkG1xWNtDW5jy2LfIA\ny19+uvP2dYSpDR08zLaghvym/LPlTmvs1gqIfXshmhul25qZeMMcrDOzgPJB0a/ZUS04dcA3vhfx\n1arocXGKS6BYYtdfEzu3WJoxUVsTngEwgq97VLZ961zsxmjFEdu+Bb9qCvi0C+SOEEGfMWZPJN4W\nxzPAzULvXbSKCV2XVuQIz4wwn+uImd5cnVu/jN/Ft1hOVmLTOvDfXQT9mnM7zCAohIBYs8p6JkV7\nO/Tbfwt+y6/l9ifvAVW7wV/9h/yAN0R73VgHNvEUaA89K7frlGt1tnjZa1jAcvMdsXZhiRpMhgwH\nO/MCYMdmpztsJ/DXF1ivmbq4jwXVOpsEN2QR8ANMAzvrok405oa7WFsr4POAjT7G2a6q3ZZVs+N6\nqAaVO4Htm6Tm+uqfgs+abj1/qiY+bdBQhzKR3/wrYMNXznOlpXdqeRFtreCzpsvXH7/befvMz1Ws\nBZ8tP4f0DKBsgHzuK5W4QnPeiGbNMZ4tVqDMf4KHWxxCr93cCL5kcVQlguAcfPYN4L89T+4wFBVs\nqCF0hyoCU4k5fxhCFTvhVOf7Po9doBwAcnLlmGCOdRmZYEceLV+3+pw161TFTKT4YHONY/RLpvxO\nYs8O8H891nl6/FAFUjTUOnbGPWvX3AJ2+XRH0ha0+sKtaGrIgSq0eVvC47R2bgF//onY2gSEK4Vi\n9WphgPboS859BUUQ676USW8SkjjMGFs6cXU0LbMWiseDCAZl/8nOleu8brhiWlmqjzD6m7E26Swm\nWuzeHlZ8PtSTib/9ipEQKqS/qRmcjTAANulH4RfxxRET2ocgwa6biF3bwO8zUi2XlHVqsbM/aPx3\nZOTLgDAD59VO728DRh0JNv5E5zkKS+3XzY3hC4khB9uvs3OAWGLsqnbHrj03SztEGNT43LshzAWY\nImSwoRHivjqZBBwxOqFE0kqZE/+Fv7b3mQuVI8bJ/5lGHTt18FcspWziKWDH/UBuqIJNZ1krI7ZR\nLprZ90+zz7PEWaxT/PORsI+JnVvB5z8E8cEi8Htvlpp4VVM7biKQlu5MtDLAWOhmRRfs2Pd/KF8Y\nrmLC0wz++N3gj98lhcnQwdTw1WcTvg+xaqksrrplA/jsGyBeeEI+A7deGXoZiPekxYG/PD9cOxiK\npxkoKQObYgRxRxn09cfvBjcEYFG337JSIBiQ7YxkdTUT99TXOvuqGUNiarG/d7I8TtXm1taAR7Me\nmpNCJIuUua+0PPw9TevcdWeUtKpoZtvXGskO2tvB/3h59M9tXCOfPSOmA3t3RhSSmXF+a4Hob5P3\n3VgPFJWCmUqb/y0zPsA6t9iZi3PTnXiR4TLTaLi7jDve+YGMTDAzwVRdiAutet69u5wKK1VhYMZo\nAZ0m0xANdU434RDliti+GbyLxXgFNyw9OzYDgoMdfGjE48w+Zlo2+O8ulJ9f9yW0mwyXLF3vskuw\nanEWVXsg2nwOK7pWNtBZT9HEqCkHIKYYO0eMIxCzmyJ/8gFrkcjSM2T8d0mZwysA5jgcRbCzrKCZ\nmcAxJwCmu5gyjwghwD9Y5Ahv4M/OhXj5aWDHFojGevDX/uEQQPj9twB7tlveNJYF2nT57GDcFy3N\n0jIRA3z1MvBVsXskRMSc44zEKdopZzrf93mNrJiGhSi/ENhXZceVpmcCefIZR3OT/d250mQZCsOy\nxCLW2zSUkxEUDuKfj8g48QgZlPnz88A/esdov1z3sJN+2PF9qnXszGdizARoE09xWuvbfOGZXI1n\nTAgBodYt9XlkVtZQStzgKz6Maf0jqnY5YjzFh/8OP0YI8Ff/YWc8ZxpYQbFVHgKAFJx2bgH/20zp\nDl+VgPIHpid8oGNLoLWWML1/1P5rvpeVDZSUOesmx8vu7UBJGVxmHWdT2dmJMMzvvB78Cac7Ng9Z\nN2Hdl8CaVU6lMOSzKzath9i+2Rrv2A9+FBYmIBa/0O0afb0REuy6iSNOY/Awu3adGscQCtNgSXZe\nRbAL+O39ptaFc2BfFdjAoWBX3Ajtr7a2GqrFLmQg1R5+HkypqScFu8iL5bAMSrFaMEwrmvGARhwQ\nMzIcGj0cdHD4MZ1Z7Or3R83SFlErtVMmTmHqQs/URpkDgOk+4jfaXl0pF31GQDabfDa0K2+Sr49S\nYiLfeVW6H8VTf8avWNnUtqsut+Z3V+KG9ldj0bRpvWNRLt55Bdi9wziXTIiD9qD127PjTwH7gSE8\ndrDIYAcfBtdTiw3BTrcn9Zq94I/OAn/iPgjVLaOhFsjJA/vxBUAgIOOk7v+TbNNn/4VYa2tD2fm/\nstvLdYi2Vogli6Sw0YFgIIwEDtpZFwEHHQIRoa+KgB/4ahXE29Lt1LRCmfBHZ1lCmnbjbGi3GeUl\njDqOYsWHTpdPXYc+/RL53KVnWIHi5u8lhAC/9UqIZ+Y4Yt34svekG6eyOAjr+3X7gIIiuXANxeVC\np9k3jf7KzWvEmG7aWsgagqVawNvpui2fA8u9aX+1zIDJucyKGEpWducWLlNQNp9VxiC+WGEvQgtL\ngEPsWFt28KH2oqIDF3A+Y5rT6qcKy3kF9utOMiua8agAZDtCreb3/xHiqQch6ms71HaLvbvAP37X\noXHmD88Ev2YqxKb1cseI74JNPCX8w1EWNezM8626btDbHW2z6pBGa4/a99T5yN/mvGcAuVMutjM9\nKmiXKjVBY3DFFBvXAEd/D+yXRp3PDizsYmsF9CvPhtix2an4NJ8N9wBbiIKi4e8gczAAIDMLrmtu\nATvFiNlpD0IEg9DvvRnivdchXpkPbtanBGyrtLdFZmf+zxuAYckR7e3OciQAsK9KjtlFxvffwQKQ\n33ol+B9+FfV9R/uf/ivE/DkxHWt9pj3otFaYwrk6x6vHmxY7I80+GzxMKlzM/pGRYSlv0NJkK0gz\nMmQ9OTMmPtKYbf4uHVmSQ2KXhBAQH78rFYH79loWszBLYyiqxU5XhE8AKC0HO91QWgQC4Qo2Yy4Q\ny9+XwoXZFq/HcjvUbpxtH7+1QoaymM9wFATXgepKsNHHQPvzX+XOCEolsexdiPffsDKes5//Jvxk\n5jw3/gT5v71dfleRMjt6PeBvPCv/v/0K9Nt/G7mBpotsZ8qh1lbgkFHQ7pKWStEQIYlYRibY0ccD\nOzZbCbbiRbQ0Wd5dAOJ2xVTHN2Z4fLHLp9sHcB4m2KGhThaAv/tGpW9nWlZDa20AJKeUQ4ohwa6L\niP3VcrJ6Tbo0aQ+/YC3itD/eZ2tfI8DS04H9NdL1Y9l79huqr7UxiJkaWNHSBJaW5nQ/UesAqQPw\n0ceDhQZTZ+fIdO+Ky5MI+CGCQdvqYeLzyMFF1YByXVpeFJcZ6LoceOtqpOvVn69GGCEJPNjgCAJv\nyIQp9lWBq8lP1AyXoYRYdoTPaxdZLhts/Q7mYoGZk4IpZBnul+JrGdOk/eJaWSx1mJEJ7KBD7ILl\ngOUSqSZniYb44lPoV02xfdeN/sHOmCrfVzOcmgv9skFgBUVgP/gRxMfvOFzUxJaNtiUmI8uyyokd\nhiD7kwttK2MsfvsuI0mCVTS+3c4epSy0xcavAY2BDRkOHD5W3vuhhqUk4HcI3ezY79tlPjgHv++P\n9vUUjaoIdUUMKJn5cvIiu0hUdiJMV+8BN5NqFJaAGVliLeHq228g/vWY8zOeZjkBqvXmTJcrJTMp\nf/we+Uy0+iCee1zWwlm/xr6fkJo4orYmsrUOkIvbjoRcISzre9vSd2RZgChusmLLRqdixlwgm8qU\nGjvjGjtohH1cMCCFXOW8piWQFZeEXygzu8M28/8sDFcINdaDP3Gvva232+5bp/4E7PxfW4IZf28h\n9N+c02EmUL7qI5n8pG4fcPhYaHc/6XQR6igNtqcZwhCStWtuBRszQX4HqgBjjEP8j5eDTzs/ejvu\nuA7i+XkQqz6SAp6/zRJqxaLngYFDwPILoKmLD7MdDXVSSG6oszPNZWTKbKQuO57IsShTY6UjoTzr\nanIYBPy2wFQ+CNrcV6EVFNrueQpMtdhlZMnPdqTJ9nnlODVqtLxuBEunEAKiarc1zolPP3RaSgxr\nE3MPCE96ZLTfOteureF9wxzLzb7eHpSZmLdW2BZF9V5NZV6bzxqLhWEpFm8+62z7rm0y5vngw8CU\nOnFh91i3H/oT91pjBjfcAfkT94GHxpIDzjk1WkmbCIj3Xgd/4E/SrfqN52yrZW5B+MHDRsgxWXCp\nAAScFllAfmfmYtvTZPchY15kY78nr1u5I0JjwgU7drLTzU3sD8nIqCoy6vbbsfz5EdqvoiZP0Tmg\naVY4A2MM2nm/kvNFMICwhFStXtkHQ0s7eFtsBV/ZQLCrbnaWpmr1dNz3a2vk9QYPs72iIs2325xJ\nxFhoHCRghVNoJxkK2fYgxPtvSm+YkEza4t1XId55FeLr/8mwjeo9zvHLupBhlaqNHNssqnZLF/A2\nn1wX5hi1EBuUZ1MV7MoMobWTEkYi2pjR0uwU7DIy5e8aa3maDxUrndk/Fdd1sb8mrE6gQ1gzn7OM\nTGhX3iQ9uQ46xBp/+B9+ldAkZb2BlAh28+bNw2233YbXX389FZfvNmL3dpkyG5ADaFGJwzrGDj0c\nLK+DAWvwMDkRtPmkKRmQnb1mr60NMxe2xoSh/SDcPzhS/Rft7iehXXlj+DWNyY//8XJia+S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h/qb7gMWlEJRDAAAaDwyunwLJiLNG8L/IbyzDxXS3Fp5PXRjs3IWf4ecs66ACwjEzVKEreSocPg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\nEuS5gtwXFUBKiyq9pqnUFuZF5HoJ2TNew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9YTe9Cl+9+iJdsn3ECXA7uJ75hZqbwdF0dR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\nwjt8AqoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x4f763160>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import talib as ta\n",
    "from fxdayu_data import DataAPI\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "DataAPI.set_file('D:/PycharmProjects/Quant_Alpha/Data_Manager/Valuation_Selection/config.py')\n",
    "hs300 = DataAPI.candle('sh000001', 'D')\n",
    "\n",
    "hs300['mom10'] = ta.abstract.MOM(hs300, 10, price='close')\n",
    "hs300['mom40'] = ta.abstract.MOM(hs300, 40, price='close')\n",
    "hs300['price_change'] = hs300.close.diff()\n",
    "hs300['Var40'] = ta.abstract.VAR(hs300, 40, price='price_change')\n",
    "hs300 = hs300.dropna()\n",
    "Div_index = hs300.mom10*hs300.mom40/hs300.Var40\n",
    "\n",
    "fig = plt.figure(figsize=(15, 7))\n",
    "plt.subplot(3,1,1)\n",
    "plt.plot(hs300.close)\n",
    "plt.subplot(3,1,2)\n",
    "plt.plot(Div_index)\n",
    "plt.hlines(-10, hs300.index[0], hs300.index[-1], linestyles='dashed', alpha=0.5)\n",
    "plt.subplot(3,1,3)\n",
    "plt.plot(hs300.mom40)\n",
    "plt.hlines(0, hs300.index[0], hs300.index[-1], linestyles='dashed', alpha=0.5)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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nkcJO377Q91l7btCgQWkmLdO3fxVFUbZu3aoMGzbsVVRB5KGctofMPkOzZ89W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P06UkFxLkISFAQCYVK09uhQ0zYIuVSE312Win98WYwty2MBgJMVd3vBm6RV1WxCLhFBb7KgqUsH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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x5839cc88>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "{'sys_analyser': {'benchmark_portfolio':               cash  market_value  static_unit_net_value  total_value  \\\n",
       "  date                                                                   \n",
       "  2005-01-04  738.21      99261.79                  1.000    100000.00   \n",
       "  2005-01-05  738.21     100248.56                  1.000    100986.77   \n",
       "  2005-01-06  738.21      99300.17                  1.010    100038.38   \n",
       "  2005-01-07  738.21      99379.96                  1.000    100118.17   \n",
       "  2005-01-10  738.21     100381.88                  1.001    101120.09   \n",
       "  2005-01-11  738.21     100711.14                  1.011    101449.35   \n",
       "  2005-01-12  738.21     100671.75                  1.014    101409.96   \n",
       "  2005-01-13  738.21     100684.88                  1.014    101423.09   \n",
       "  2005-01-14  738.21      99819.31                  1.014    100557.52   \n",
       "  2005-01-17  738.21      97712.45                  1.006     98450.66   \n",
       "  2005-01-18  738.21      98443.69                  0.985     99181.90   \n",
       "  2005-01-19  738.21      97688.21                  0.992     98426.42   \n",
       "  2005-01-20  738.21      96581.25                  0.984     97319.46   \n",
       "  2005-01-21  738.21      99242.60                  0.973     99980.81   \n",
       "  2005-01-24  738.21     100811.13                  1.000    101549.34   \n",
       "  2005-01-25  738.21     100775.78                  1.015    101513.99   \n",
       "  2005-01-26  738.21      99982.93                  1.015    100721.14   \n",
       "  2005-01-27  738.21      98437.63                  1.007     99175.84   \n",
       "  2005-01-28  738.21      97890.21                  0.992     98628.42   \n",
       "  2005-01-31  738.21      96442.88                  0.986     97181.09   \n",
       "  2005-02-01  738.21      96550.95                  0.972     97289.16   \n",
       "  2005-02-02  738.21     101697.91                  0.973    102436.12   \n",
       "  2005-02-03  738.21     100315.22                  1.024    101053.43   \n",
       "  2005-02-04  738.21     102702.86                  1.011    103441.07   \n",
       "  2005-02-16  738.21     103381.58                  1.034    104119.79   \n",
       "  2005-02-17  738.21     103081.61                  1.041    103819.82   \n",
       "  2005-02-18  738.21     101612.06                  1.038    102350.27   \n",
       "  2005-02-21  738.21     103588.63                  1.024    104326.84   \n",
       "  2005-02-22  738.21     105720.74                  1.043    106458.95   \n",
       "  2005-02-23  738.21     105437.94                  1.065    106176.15   \n",
       "  ...            ...           ...                    ...          ...   \n",
       "  2016-10-21  738.21     336101.74                  3.359    336839.95   \n",
       "  2016-10-24  738.21     340125.58                  3.368    340863.79   \n",
       "  2016-10-25  738.21     340112.45                  3.409    340850.66   \n",
       "  2016-10-26  738.21     338834.80                  3.409    339573.01   \n",
       "  2016-10-27  738.21     337915.70                  3.396    338653.91   \n",
       "  2016-10-28  738.21     337353.13                  3.387    338091.34   \n",
       "  2016-10-31  738.21     336964.28                  3.381    337702.49   \n",
       "  2016-11-01  738.21     339264.05                  3.377    340002.26   \n",
       "  2016-11-02  738.21     336668.35                  3.400    337406.56   \n",
       "  2016-11-03  738.21     339873.08                  3.374    340611.29   \n",
       "  2016-11-04  738.21     338771.17                  3.406    339509.38   \n",
       "  2016-11-07  738.21     339015.59                  3.395    339753.80   \n",
       "  2016-11-08  738.21     340483.12                  3.398    341221.33   \n",
       "  2016-11-09  738.21     338658.05                  3.412    339396.26   \n",
       "  2016-11-10  738.21     342451.61                  3.394    343189.82   \n",
       "  2016-11-11  738.21     345139.22                  3.432    345877.43   \n",
       "  2016-11-14  738.21     346455.25                  3.459    347193.46   \n",
       "  2016-11-15  738.21     346416.87                  3.472    347155.08   \n",
       "  2016-11-16  738.21     346388.59                  3.472    347126.80   \n",
       "  2016-11-17  738.21     347090.54                  3.471    347828.75   \n",
       "  2016-11-18  738.21     345163.46                  3.478    345901.67   \n",
       "  2016-11-21  738.21     347552.11                  3.459    348290.32   \n",
       "  2016-11-22  738.21     350304.36                  3.483    351042.57   \n",
       "  2016-11-23  738.21     350947.73                  3.510    351685.94   \n",
       "  2016-11-24  738.21     352362.74                  3.517    353100.95   \n",
       "  2016-11-25  738.21     355651.30                  3.531    356389.51   \n",
       "  2016-11-28  738.21     357043.08                  3.564    357781.29   \n",
       "  2016-11-29  738.21     359968.04                  3.578    360706.25   \n",
       "  2016-11-30  738.21     357338.00                  3.607    358076.21   \n",
       "  2016-12-01  738.21     360069.04                  3.581    360807.25   \n",
       "  \n",
       "              unit_net_value   units  \n",
       "  date                                \n",
       "  2005-01-04        1.000000  100000  \n",
       "  2005-01-05        1.009868  100000  \n",
       "  2005-01-06        1.000384  100000  \n",
       "  2005-01-07        1.001182  100000  \n",
       "  2005-01-10        1.011201  100000  \n",
       "  2005-01-11        1.014494  100000  \n",
       "  2005-01-12        1.014100  100000  \n",
       "  2005-01-13        1.014231  100000  \n",
       "  2005-01-14        1.005575  100000  \n",
       "  2005-01-17        0.984507  100000  \n",
       "  2005-01-18        0.991819  100000  \n",
       "  2005-01-19        0.984264  100000  \n",
       "  2005-01-20        0.973195  100000  \n",
       "  2005-01-21        0.999808  100000  \n",
       "  2005-01-24        1.015493  100000  \n",
       "  2005-01-25        1.015140  100000  \n",
       "  2005-01-26        1.007211  100000  \n",
       "  2005-01-27        0.991758  100000  \n",
       "  2005-01-28        0.986284  100000  \n",
       "  2005-01-31        0.971811  100000  \n",
       "  2005-02-01        0.972892  100000  \n",
       "  2005-02-02        1.024361  100000  \n",
       "  2005-02-03        1.010534  100000  \n",
       "  2005-02-04        1.034411  100000  \n",
       "  2005-02-16        1.041198  100000  \n",
       "  2005-02-17        1.038198  100000  \n",
       "  2005-02-18        1.023503  100000  \n",
       "  2005-02-21        1.043268  100000  \n",
       "  2005-02-22        1.064590  100000  \n",
       "  2005-02-23        1.061762  100000  \n",
       "  ...                    ...     ...  \n",
       "  2016-10-21        3.368400  100000  \n",
       "  2016-10-24        3.408638  100000  \n",
       "  2016-10-25        3.408507  100000  \n",
       "  2016-10-26        3.395730  100000  \n",
       "  2016-10-27        3.386539  100000  \n",
       "  2016-10-28        3.380913  100000  \n",
       "  2016-10-31        3.377025  100000  \n",
       "  2016-11-01        3.400023  100000  \n",
       "  2016-11-02        3.374066  100000  \n",
       "  2016-11-03        3.406113  100000  \n",
       "  2016-11-04        3.395094  100000  \n",
       "  2016-11-07        3.397538  100000  \n",
       "  2016-11-08        3.412213  100000  \n",
       "  2016-11-09        3.393963  100000  \n",
       "  2016-11-10        3.431898  100000  \n",
       "  2016-11-11        3.458774  100000  \n",
       "  2016-11-14        3.471935  100000  \n",
       "  2016-11-15        3.471551  100000  \n",
       "  2016-11-16        3.471268  100000  \n",
       "  2016-11-17        3.478287  100000  \n",
       "  2016-11-18        3.459017  100000  \n",
       "  2016-11-21        3.482903  100000  \n",
       "  2016-11-22        3.510426  100000  \n",
       "  2016-11-23        3.516859  100000  \n",
       "  2016-11-24        3.531010  100000  \n",
       "  2016-11-25        3.563895  100000  \n",
       "  2016-11-28        3.577813  100000  \n",
       "  2016-11-29        3.607063  100000  \n",
       "  2016-11-30        3.580762  100000  \n",
       "  2016-12-01        3.608073  100000  \n",
       "  \n",
       "  [2894 rows x 6 columns],\n",
       "  'portfolio':                   cash  market_value  static_unit_net_value  total_value  \\\n",
       "  date                                                                       \n",
       "  2005-01-04  100000.000           0.0                  1.000   100000.000   \n",
       "  2005-01-05  100000.000           0.0                  1.000   100000.000   \n",
       "  2005-01-06  100000.000           0.0                  1.000   100000.000   \n",
       "  2005-01-07  100000.000           0.0                  1.000   100000.000   \n",
       "  2005-01-10  100000.000           0.0                  1.000   100000.000   \n",
       "  2005-01-11  100000.000           0.0                  1.000   100000.000   \n",
       "  2005-01-12  100000.000           0.0                  1.000   100000.000   \n",
       "  2005-01-13  100000.000           0.0                  1.000   100000.000   \n",
       "  2005-01-14  100000.000           0.0                  1.000   100000.000   \n",
       "  2005-01-17  100000.000           0.0                  1.000   100000.000   \n",
       "  2005-01-18  100000.000           0.0                  1.000   100000.000   \n",
       "  2005-01-19  100000.000           0.0                  1.000   100000.000   \n",
       "  2005-01-20  100000.000           0.0                  1.000   100000.000   \n",
       "  2005-01-21  100000.000           0.0                  1.000   100000.000   \n",
       "  2005-01-24  100000.000           0.0                  1.000   100000.000   \n",
       "  2005-01-25  100000.000           0.0                  1.000   100000.000   \n",
       "  2005-01-26  100000.000           0.0                  1.000   100000.000   \n",
       "  2005-01-27  100000.000           0.0                  1.000   100000.000   \n",
       "  2005-01-28  100000.000           0.0                  1.000   100000.000   \n",
       "  2005-01-31  100000.000           0.0                  1.000   100000.000   \n",
       "  2005-02-01  100000.000           0.0                  1.000   100000.000   \n",
       "  2005-02-02  100000.000           0.0                  1.000   100000.000   \n",
       "  2005-02-03  100000.000           0.0                  1.000   100000.000   \n",
       "  2005-02-04  100000.000           0.0                  1.000   100000.000   \n",
       "  2005-02-16  100000.000           0.0                  1.000   100000.000   \n",
       "  2005-02-17  100000.000           0.0                  1.000   100000.000   \n",
       "  2005-02-18  100000.000           0.0                  1.000   100000.000   \n",
       "  2005-02-21  100000.000           0.0                  1.000   100000.000   \n",
       "  2005-02-22  100000.000           0.0                  1.000   100000.000   \n",
       "  2005-02-23  100000.000           0.0                  1.000   100000.000   \n",
       "  ...                ...           ...                    ...          ...   \n",
       "  2016-10-21  170251.185       17529.6                  1.877   187780.785   \n",
       "  2016-10-24  170251.185       17740.8                  1.878   187991.985   \n",
       "  2016-10-25  170251.185       17683.2                  1.880   187934.385   \n",
       "  2016-10-26  170251.185       17568.0                  1.879   187819.185   \n",
       "  2016-10-27  170251.185       17587.2                  1.878   187838.385   \n",
       "  2016-10-28  170251.185       17606.4                  1.878   187857.585   \n",
       "  2016-10-31  170251.185       17568.0                  1.879   187819.185   \n",
       "  2016-11-01  170251.185       17548.8                  1.878   187799.985   \n",
       "  2016-11-02  170251.185       17414.4                  1.878   187665.585   \n",
       "  2016-11-03  170251.185       17529.6                  1.877   187780.785   \n",
       "  2016-11-04  170251.185       17491.2                  1.878   187742.385   \n",
       "  2016-11-07  170251.185       17510.4                  1.877   187761.585   \n",
       "  2016-11-08  170251.185       17568.0                  1.878   187819.185   \n",
       "  2016-11-09  170251.185       17414.4                  1.878   187665.585   \n",
       "  2016-11-10  170251.185       17548.8                  1.877   187799.985   \n",
       "  2016-11-11  170251.185       17625.6                  1.878   187876.785   \n",
       "  2016-11-14  170251.185       17702.4                  1.879   187953.585   \n",
       "  2016-11-15  170251.185       17721.6                  1.880   187972.785   \n",
       "  2016-11-16  170251.185       17721.6                  1.880   187972.785   \n",
       "  2016-11-17  170251.185       17683.2                  1.880   187934.385   \n",
       "  2016-11-18  170251.185       17625.6                  1.879   187876.785   \n",
       "  2016-11-21  170251.185       17740.8                  1.879   187991.985   \n",
       "  2016-11-22  170251.185       17971.2                  1.880   188222.385   \n",
       "  2016-11-23  170251.185       18144.0                  1.882   188395.185   \n",
       "  2016-11-24  170251.185       18182.4                  1.884   188433.585   \n",
       "  2016-11-25  170251.185       18470.4                  1.884   188721.585   \n",
       "  2016-11-28  170251.185       18489.6                  1.887   188740.785   \n",
       "  2016-11-29  170251.185       18470.4                  1.887   188721.585   \n",
       "  2016-11-30  170251.185       18336.0                  1.887   188587.185   \n",
       "  2016-12-01  170251.185       18432.0                  1.886   188683.185   \n",
       "  \n",
       "              unit_net_value   units  \n",
       "  date                                \n",
       "  2005-01-04        1.000000  100000  \n",
       "  2005-01-05        1.000000  100000  \n",
       "  2005-01-06        1.000000  100000  \n",
       "  2005-01-07        1.000000  100000  \n",
       "  2005-01-10        1.000000  100000  \n",
       "  2005-01-11        1.000000  100000  \n",
       "  2005-01-12        1.000000  100000  \n",
       "  2005-01-13        1.000000  100000  \n",
       "  2005-01-14        1.000000  100000  \n",
       "  2005-01-17        1.000000  100000  \n",
       "  2005-01-18        1.000000  100000  \n",
       "  2005-01-19        1.000000  100000  \n",
       "  2005-01-20        1.000000  100000  \n",
       "  2005-01-21        1.000000  100000  \n",
       "  2005-01-24        1.000000  100000  \n",
       "  2005-01-25        1.000000  100000  \n",
       "  2005-01-26        1.000000  100000  \n",
       "  2005-01-27        1.000000  100000  \n",
       "  2005-01-28        1.000000  100000  \n",
       "  2005-01-31        1.000000  100000  \n",
       "  2005-02-01        1.000000  100000  \n",
       "  2005-02-02        1.000000  100000  \n",
       "  2005-02-03        1.000000  100000  \n",
       "  2005-02-04        1.000000  100000  \n",
       "  2005-02-16        1.000000  100000  \n",
       "  2005-02-17        1.000000  100000  \n",
       "  2005-02-18        1.000000  100000  \n",
       "  2005-02-21        1.000000  100000  \n",
       "  2005-02-22        1.000000  100000  \n",
       "  2005-02-23        1.000000  100000  \n",
       "  ...                    ...     ...  \n",
       "  2016-10-21        1.877808  100000  \n",
       "  2016-10-24        1.879920  100000  \n",
       "  2016-10-25        1.879344  100000  \n",
       "  2016-10-26        1.878192  100000  \n",
       "  2016-10-27        1.878384  100000  \n",
       "  2016-10-28        1.878576  100000  \n",
       "  2016-10-31        1.878192  100000  \n",
       "  2016-11-01        1.878000  100000  \n",
       "  2016-11-02        1.876656  100000  \n",
       "  2016-11-03        1.877808  100000  \n",
       "  2016-11-04        1.877424  100000  \n",
       "  2016-11-07        1.877616  100000  \n",
       "  2016-11-08        1.878192  100000  \n",
       "  2016-11-09        1.876656  100000  \n",
       "  2016-11-10        1.878000  100000  \n",
       "  2016-11-11        1.878768  100000  \n",
       "  2016-11-14        1.879536  100000  \n",
       "  2016-11-15        1.879728  100000  \n",
       "  2016-11-16        1.879728  100000  \n",
       "  2016-11-17        1.879344  100000  \n",
       "  2016-11-18        1.878768  100000  \n",
       "  2016-11-21        1.879920  100000  \n",
       "  2016-11-22        1.882224  100000  \n",
       "  2016-11-23        1.883952  100000  \n",
       "  2016-11-24        1.884336  100000  \n",
       "  2016-11-25        1.887216  100000  \n",
       "  2016-11-28        1.887408  100000  \n",
       "  2016-11-29        1.887216  100000  \n",
       "  2016-11-30        1.885872  100000  \n",
       "  2016-12-01        1.886832  100000  \n",
       "  \n",
       "  [2894 rows x 6 columns],\n",
       "  'stock_account':                   cash  dividend_receivable  market_value  total_value  \\\n",
       "  date                                                                     \n",
       "  2005-01-04  100000.000                    0           0.0   100000.000   \n",
       "  2005-01-05  100000.000                    0           0.0   100000.000   \n",
       "  2005-01-06  100000.000                    0           0.0   100000.000   \n",
       "  2005-01-07  100000.000                    0           0.0   100000.000   \n",
       "  2005-01-10  100000.000                    0           0.0   100000.000   \n",
       "  2005-01-11  100000.000                    0           0.0   100000.000   \n",
       "  2005-01-12  100000.000                    0           0.0   100000.000   \n",
       "  2005-01-13  100000.000                    0           0.0   100000.000   \n",
       "  2005-01-14  100000.000                    0           0.0   100000.000   \n",
       "  2005-01-17  100000.000                    0           0.0   100000.000   \n",
       "  2005-01-18  100000.000                    0           0.0   100000.000   \n",
       "  2005-01-19  100000.000                    0           0.0   100000.000   \n",
       "  2005-01-20  100000.000                    0           0.0   100000.000   \n",
       "  2005-01-21  100000.000                    0           0.0   100000.000   \n",
       "  2005-01-24  100000.000                    0           0.0   100000.000   \n",
       "  2005-01-25  100000.000                    0           0.0   100000.000   \n",
       "  2005-01-26  100000.000                    0           0.0   100000.000   \n",
       "  2005-01-27  100000.000                    0           0.0   100000.000   \n",
       "  2005-01-28  100000.000                    0           0.0   100000.000   \n",
       "  2005-01-31  100000.000                    0           0.0   100000.000   \n",
       "  2005-02-01  100000.000                    0           0.0   100000.000   \n",
       "  2005-02-02  100000.000                    0           0.0   100000.000   \n",
       "  2005-02-03  100000.000                    0           0.0   100000.000   \n",
       "  2005-02-04  100000.000                    0           0.0   100000.000   \n",
       "  2005-02-16  100000.000                    0           0.0   100000.000   \n",
       "  2005-02-17  100000.000                    0           0.0   100000.000   \n",
       "  2005-02-18  100000.000                    0           0.0   100000.000   \n",
       "  2005-02-21  100000.000                    0           0.0   100000.000   \n",
       "  2005-02-22  100000.000                    0           0.0   100000.000   \n",
       "  2005-02-23  100000.000                    0           0.0   100000.000   \n",
       "  ...                ...                  ...           ...          ...   \n",
       "  2016-10-21  170251.185                    0       17529.6   187780.785   \n",
       "  2016-10-24  170251.185                    0       17740.8   187991.985   \n",
       "  2016-10-25  170251.185                    0       17683.2   187934.385   \n",
       "  2016-10-26  170251.185                    0       17568.0   187819.185   \n",
       "  2016-10-27  170251.185                    0       17587.2   187838.385   \n",
       "  2016-10-28  170251.185                    0       17606.4   187857.585   \n",
       "  2016-10-31  170251.185                    0       17568.0   187819.185   \n",
       "  2016-11-01  170251.185                    0       17548.8   187799.985   \n",
       "  2016-11-02  170251.185                    0       17414.4   187665.585   \n",
       "  2016-11-03  170251.185                    0       17529.6   187780.785   \n",
       "  2016-11-04  170251.185                    0       17491.2   187742.385   \n",
       "  2016-11-07  170251.185                    0       17510.4   187761.585   \n",
       "  2016-11-08  170251.185                    0       17568.0   187819.185   \n",
       "  2016-11-09  170251.185                    0       17414.4   187665.585   \n",
       "  2016-11-10  170251.185                    0       17548.8   187799.985   \n",
       "  2016-11-11  170251.185                    0       17625.6   187876.785   \n",
       "  2016-11-14  170251.185                    0       17702.4   187953.585   \n",
       "  2016-11-15  170251.185                    0       17721.6   187972.785   \n",
       "  2016-11-16  170251.185                    0       17721.6   187972.785   \n",
       "  2016-11-17  170251.185                    0       17683.2   187934.385   \n",
       "  2016-11-18  170251.185                    0       17625.6   187876.785   \n",
       "  2016-11-21  170251.185                    0       17740.8   187991.985   \n",
       "  2016-11-22  170251.185                    0       17971.2   188222.385   \n",
       "  2016-11-23  170251.185                    0       18144.0   188395.185   \n",
       "  2016-11-24  170251.185                    0       18182.4   188433.585   \n",
       "  2016-11-25  170251.185                    0       18470.4   188721.585   \n",
       "  2016-11-28  170251.185                    0       18489.6   188740.785   \n",
       "  2016-11-29  170251.185                    0       18470.4   188721.585   \n",
       "  2016-11-30  170251.185                    0       18336.0   188587.185   \n",
       "  2016-12-01  170251.185                    0       18432.0   188683.185   \n",
       "  \n",
       "              transaction_cost  \n",
       "  date                          \n",
       "  2005-01-04               0.0  \n",
       "  2005-01-05               0.0  \n",
       "  2005-01-06               0.0  \n",
       "  2005-01-07               0.0  \n",
       "  2005-01-10               0.0  \n",
       "  2005-01-11               0.0  \n",
       "  2005-01-12               0.0  \n",
       "  2005-01-13               0.0  \n",
       "  2005-01-14               0.0  \n",
       "  2005-01-17               0.0  \n",
       "  2005-01-18               0.0  \n",
       "  2005-01-19               0.0  \n",
       "  2005-01-20               0.0  \n",
       "  2005-01-21               0.0  \n",
       "  2005-01-24               0.0  \n",
       "  2005-01-25               0.0  \n",
       "  2005-01-26               0.0  \n",
       "  2005-01-27               0.0  \n",
       "  2005-01-28               0.0  \n",
       "  2005-01-31               0.0  \n",
       "  2005-02-01               0.0  \n",
       "  2005-02-02               0.0  \n",
       "  2005-02-03               0.0  \n",
       "  2005-02-04               0.0  \n",
       "  2005-02-16               0.0  \n",
       "  2005-02-17               0.0  \n",
       "  2005-02-18               0.0  \n",
       "  2005-02-21               0.0  \n",
       "  2005-02-22               0.0  \n",
       "  2005-02-23               0.0  \n",
       "  ...                      ...  \n",
       "  2016-10-21               0.0  \n",
       "  2016-10-24               0.0  \n",
       "  2016-10-25               0.0  \n",
       "  2016-10-26               0.0  \n",
       "  2016-10-27               0.0  \n",
       "  2016-10-28               0.0  \n",
       "  2016-10-31               0.0  \n",
       "  2016-11-01               0.0  \n",
       "  2016-11-02               0.0  \n",
       "  2016-11-03               0.0  \n",
       "  2016-11-04               0.0  \n",
       "  2016-11-07               0.0  \n",
       "  2016-11-08               0.0  \n",
       "  2016-11-09               0.0  \n",
       "  2016-11-10               0.0  \n",
       "  2016-11-11               0.0  \n",
       "  2016-11-14               0.0  \n",
       "  2016-11-15               0.0  \n",
       "  2016-11-16               0.0  \n",
       "  2016-11-17               0.0  \n",
       "  2016-11-18               0.0  \n",
       "  2016-11-21               0.0  \n",
       "  2016-11-22               0.0  \n",
       "  2016-11-23               0.0  \n",
       "  2016-11-24               0.0  \n",
       "  2016-11-25               0.0  \n",
       "  2016-11-28               0.0  \n",
       "  2016-11-29               0.0  \n",
       "  2016-11-30               0.0  \n",
       "  2016-12-01               0.0  \n",
       "  \n",
       "  [2894 rows x 5 columns],\n",
       "  'stock_positions':             avg_price  last_price  market_value order_book_id  quantity symbol\n",
       "  date                                                                          \n",
       "  2005-06-01      5.950        5.95       16660.0   000001.XSHE    2800.0   平安银行\n",
       "  2005-06-02      5.950        5.78       16184.0   000001.XSHE    2800.0   平安银行\n",
       "  2005-06-03      5.950        5.83       16324.0   000001.XSHE    2800.0   平安银行\n",
       "  2005-06-06      5.950        5.94       16632.0   000001.XSHE    2800.0   平安银行\n",
       "  2005-06-07      5.950        5.94       16632.0   000001.XSHE    2800.0   平安银行\n",
       "  2005-06-08      5.950        6.49       18172.0   000001.XSHE    2800.0   平安银行\n",
       "  2005-06-09      5.950        6.48       18144.0   000001.XSHE    2800.0   平安银行\n",
       "  2005-06-10      5.950        6.58       18424.0   000001.XSHE    2800.0   平安银行\n",
       "  2005-06-13      5.950        6.50       18200.0   000001.XSHE    2800.0   平安银行\n",
       "  2005-06-14      5.950        6.39       17892.0   000001.XSHE    2800.0   平安银行\n",
       "  2005-06-15      5.950        6.22       17416.0   000001.XSHE    2800.0   平安银行\n",
       "  2005-06-16      5.950        6.37       17836.0   000001.XSHE    2800.0   平安银行\n",
       "  2005-06-17      5.950        6.37       17836.0   000001.XSHE    2800.0   平安银行\n",
       "  2005-06-20      5.950        6.39       17892.0   000001.XSHE    2800.0   平安银行\n",
       "  2005-06-21      5.950        6.39       17892.0   000001.XSHE    2800.0   平安银行\n",
       "  2005-06-22      5.950        6.48       18144.0   000001.XSHE    2800.0   平安银行\n",
       "  2005-06-23      5.950        6.23       17444.0   000001.XSHE    2800.0   平安银行\n",
       "  2005-06-24      5.950        6.29       17612.0   000001.XSHE    2800.0   平安银行\n",
       "  2005-06-27      5.950        6.42       17976.0   000001.XSHE    2800.0   平安银行\n",
       "  2005-06-28      5.950        6.25       17500.0   000001.XSHE    2800.0   平安银行\n",
       "  2005-06-29      5.950        6.22       17416.0   000001.XSHE    2800.0   平安银行\n",
       "  2005-06-30      5.950        5.93       16604.0   000001.XSHE    2800.0   平安银行\n",
       "  2005-07-01      5.950        5.79       16212.0   000001.XSHE    2800.0   平安银行\n",
       "  2005-07-04      5.950        5.84       16352.0   000001.XSHE    2800.0   平安银行\n",
       "  2005-07-05      5.950        5.76       16128.0   000001.XSHE    2800.0   平安银行\n",
       "  2005-07-06      5.950        5.67       15876.0   000001.XSHE    2800.0   平安银行\n",
       "  2005-07-07      5.950        5.66       15848.0   000001.XSHE    2800.0   平安银行\n",
       "  2005-07-08      5.950        5.46       15288.0   000001.XSHE    2800.0   平安银行\n",
       "  2005-07-11      5.950        5.49       15372.0   000001.XSHE    2800.0   平安银行\n",
       "  2005-07-12      5.950        5.81       16268.0   000001.XSHE    2800.0   平安银行\n",
       "  ...               ...         ...           ...           ...       ...    ...\n",
       "  2016-10-21      8.789        9.13       17529.6   000001.XSHE    1920.0   平安银行\n",
       "  2016-10-24      8.789        9.24       17740.8   000001.XSHE    1920.0   平安银行\n",
       "  2016-10-25      8.789        9.21       17683.2   000001.XSHE    1920.0   平安银行\n",
       "  2016-10-26      8.789        9.15       17568.0   000001.XSHE    1920.0   平安银行\n",
       "  2016-10-27      8.789        9.16       17587.2   000001.XSHE    1920.0   平安银行\n",
       "  2016-10-28      8.789        9.17       17606.4   000001.XSHE    1920.0   平安银行\n",
       "  2016-10-31      8.789        9.15       17568.0   000001.XSHE    1920.0   平安银行\n",
       "  2016-11-01      8.789        9.14       17548.8   000001.XSHE    1920.0   平安银行\n",
       "  2016-11-02      8.789        9.07       17414.4   000001.XSHE    1920.0   平安银行\n",
       "  2016-11-03      8.789        9.13       17529.6   000001.XSHE    1920.0   平安银行\n",
       "  2016-11-04      8.789        9.11       17491.2   000001.XSHE    1920.0   平安银行\n",
       "  2016-11-07      8.789        9.12       17510.4   000001.XSHE    1920.0   平安银行\n",
       "  2016-11-08      8.789        9.15       17568.0   000001.XSHE    1920.0   平安银行\n",
       "  2016-11-09      8.789        9.07       17414.4   000001.XSHE    1920.0   平安银行\n",
       "  2016-11-10      8.789        9.14       17548.8   000001.XSHE    1920.0   平安银行\n",
       "  2016-11-11      8.789        9.18       17625.6   000001.XSHE    1920.0   平安银行\n",
       "  2016-11-14      8.789        9.22       17702.4   000001.XSHE    1920.0   平安银行\n",
       "  2016-11-15      8.789        9.23       17721.6   000001.XSHE    1920.0   平安银行\n",
       "  2016-11-16      8.789        9.23       17721.6   000001.XSHE    1920.0   平安银行\n",
       "  2016-11-17      8.789        9.21       17683.2   000001.XSHE    1920.0   平安银行\n",
       "  2016-11-18      8.789        9.18       17625.6   000001.XSHE    1920.0   平安银行\n",
       "  2016-11-21      8.789        9.24       17740.8   000001.XSHE    1920.0   平安银行\n",
       "  2016-11-22      8.789        9.36       17971.2   000001.XSHE    1920.0   平安银行\n",
       "  2016-11-23      8.789        9.45       18144.0   000001.XSHE    1920.0   平安银行\n",
       "  2016-11-24      8.789        9.47       18182.4   000001.XSHE    1920.0   平安银行\n",
       "  2016-11-25      8.789        9.62       18470.4   000001.XSHE    1920.0   平安银行\n",
       "  2016-11-28      8.789        9.63       18489.6   000001.XSHE    1920.0   平安银行\n",
       "  2016-11-29      8.789        9.62       18470.4   000001.XSHE    1920.0   平安银行\n",
       "  2016-11-30      8.789        9.55       18336.0   000001.XSHE    1920.0   平安银行\n",
       "  2016-12-01      8.789        9.60       18432.0   000001.XSHE    1920.0   平安银行\n",
       "  \n",
       "  [2474 rows x 6 columns],\n",
       "  'summary': {'alpha': -0.007,\n",
       "   'annualized_returns': 0.055,\n",
       "   'benchmark': '000300.XSHG',\n",
       "   'benchmark_annualized_returns': 0.114,\n",
       "   'benchmark_total_returns': 2.608,\n",
       "   'beta': 0.107,\n",
       "   'cash': 170251.185,\n",
       "   'downside_risk': 0.18,\n",
       "   'end_date': '2016-12-01',\n",
       "   'future_starting_cash': 0,\n",
       "   'information_ratio': -0.359,\n",
       "   'max_drawdown': 0.11,\n",
       "   'run_type': 'BACKTEST',\n",
       "   'sharpe': 0.052,\n",
       "   'sortino': 0.018,\n",
       "   'start_date': '2005-01-04',\n",
       "   'stock_starting_cash': 100000,\n",
       "   'strategy_file': 'strategy.py',\n",
       "   'strategy_name': 'strategy',\n",
       "   'total_returns': 0.887,\n",
       "   'total_value': 188683.185,\n",
       "   'tracking_error': 0.262,\n",
       "   'unit_net_value': 1.887,\n",
       "   'units': 100000,\n",
       "   'volatility': 0.064},\n",
       "  'trades':                      commission     exec_id  last_price  last_quantity  \\\n",
       "  datetime                                                                 \n",
       "  2005-06-01 15:00:00   13.328000  1498157492        5.95         2800.0   \n",
       "  2007-04-25 15:00:00   55.350400  1498157493       24.71         2800.0   \n",
       "  2007-07-05 15:00:00    5.000000  1498157494       25.20          200.0   \n",
       "  2008-04-21 15:00:00    5.000000  1498157495       22.41          200.0   \n",
       "  2008-05-15 15:00:00    5.000000  1498157496       27.18          200.0   \n",
       "  2008-06-11 15:00:00    5.000000  1498157497       21.20          200.0   \n",
       "  2008-12-22 15:00:00   11.536000  1498157498       10.30         1400.0   \n",
       "  2015-04-13 15:00:00   42.681139  1498157499       16.54         3225.6   \n",
       "  2015-04-24 15:00:00    9.038400  1498157500       16.14          700.0   \n",
       "  2015-06-26 15:00:00    7.711200  1498157501       13.77          700.0   \n",
       "  2015-11-03 15:00:00   13.260000  1498157502       11.05         1500.0   \n",
       "  2016-01-26 15:00:00   11.844000  1498157503        9.87         1500.0   \n",
       "  2016-04-05 15:00:00   13.696000  1498157504       10.70         1600.0   \n",
       "  \n",
       "                      order_book_id    order_id position_effect  side symbol  \\\n",
       "  datetime                                                                     \n",
       "  2005-06-01 15:00:00   000001.XSHE  1498158907            None   BUY   平安银行   \n",
       "  2007-04-25 15:00:00   000001.XSHE  1498158908            None  SELL   平安银行   \n",
       "  2007-07-05 15:00:00   000001.XSHE  1498158909            None   BUY   平安银行   \n",
       "  2008-04-21 15:00:00   000001.XSHE  1498158910            None  SELL   平安银行   \n",
       "  2008-05-15 15:00:00   000001.XSHE  1498158911            None   BUY   平安银行   \n",
       "  2008-06-11 15:00:00   000001.XSHE  1498158913            None  SELL   平安银行   \n",
       "  2008-12-22 15:00:00   000001.XSHE  1498158914            None   BUY   平安银行   \n",
       "  2015-04-13 15:00:00   000001.XSHE  1498158915            None  SELL   平安银行   \n",
       "  2015-04-24 15:00:00   000001.XSHE  1498158916            None   BUY   平安银行   \n",
       "  2015-06-26 15:00:00   000001.XSHE  1498158917            None  SELL   平安银行   \n",
       "  2015-11-03 15:00:00   000001.XSHE  1498158918            None   BUY   平安银行   \n",
       "  2016-01-26 15:00:00   000001.XSHE  1498158919            None  SELL   平安银行   \n",
       "  2016-04-05 15:00:00   000001.XSHE  1498158920            None   BUY   平安银行   \n",
       "  \n",
       "                             tax     trading_datetime  transaction_cost  \n",
       "  datetime                                                               \n",
       "  2005-06-01 15:00:00   0.000000  2005-06-01 15:00:00         13.328000  \n",
       "  2007-04-25 15:00:00  69.188000  2007-04-25 15:00:00        124.538400  \n",
       "  2007-07-05 15:00:00   0.000000  2007-07-05 15:00:00          5.000000  \n",
       "  2008-04-21 15:00:00   4.482000  2008-04-21 15:00:00          9.482000  \n",
       "  2008-05-15 15:00:00   0.000000  2008-05-15 15:00:00          5.000000  \n",
       "  2008-06-11 15:00:00   4.240000  2008-06-11 15:00:00          9.240000  \n",
       "  2008-12-22 15:00:00   0.000000  2008-12-22 15:00:00         11.536000  \n",
       "  2015-04-13 15:00:00  53.351424  2015-04-13 15:00:00         96.032563  \n",
       "  2015-04-24 15:00:00   0.000000  2015-04-24 15:00:00          9.038400  \n",
       "  2015-06-26 15:00:00   9.639000  2015-06-26 15:00:00         17.350200  \n",
       "  2015-11-03 15:00:00   0.000000  2015-11-03 15:00:00         13.260000  \n",
       "  2016-01-26 15:00:00  14.805000  2016-01-26 15:00:00         26.649000  \n",
       "  2016-04-05 15:00:00   0.000000  2016-04-05 15:00:00         13.696000  }}"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#coding=utf-8\n",
    "# run_code_demo\n",
    "from rqalpha import run_code\n",
    "\n",
    "code = \"\"\"\n",
    "import rqalpha\n",
    "from rqalpha.api import *\n",
    "import talib as ta\n",
    "import os\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "def init(context):\n",
    "    update_universe('000001.XSHE')\n",
    "    context.s1 = \"000001.XSHE\"\n",
    "    context.LongPeriod = 50\n",
    "    context.stoplossmultipler= 0.90 #止损 乘数\n",
    "    context.takepofitmultipler= 4 #止盈 乘数\n",
    "\n",
    "def handle_bar(context, bar_dict):\n",
    "    entry_exit(context, bar_dict)\n",
    "\n",
    "def entry_exit(context, bar_dict):\n",
    "    stop_loss(context, bar_dict)\n",
    "    prices = history_bars(context.s1, context.LongPeriod+2, '1d', 'close')\n",
    "    if len(prices)>=context.LongPeriod+2:\n",
    "        mom10 = ta.MOM(prices, 10)\n",
    "        mom40 = ta.MOM(prices, 40)\n",
    "        P_C = np.diff(prices)\n",
    "        Var = ta.VAR(P_C, 40)\n",
    "        Div_index = mom10[-1]*mom40[-1]/Var[-1]\n",
    "        # print 'mom10:',mom10\n",
    "        # print 'mom40:',mom40\n",
    "        # print 'Price_Change:', P_C\n",
    "        # print 'Var:', Var\n",
    "\n",
    "\n",
    "        cur_position = context.portfolio.positions[context.s1].quantity\n",
    "        shares = context.portfolio.cash/bar_dict[context.s1].close\n",
    "        EMA_S = ta.EMA(prices, 15)\n",
    "        EMA_L = ta.EMA(prices, context.LongPeriod)\n",
    "\n",
    "        # if EMA_S[-1] < EMA_L[-1] and EMA_S[-2] > EMA_L[-2]:\n",
    "        #     order_target_value(context.s1, 0)\n",
    "\n",
    "        if Div_index < -1 and mom40[-1]>0 and cur_position == 0:\n",
    "            order_target_value(context.s1, shares)\n",
    "\n",
    "def stop_loss(context,bar_dict):\n",
    "    for stock in context.portfolio.positions:\n",
    "        if bar_dict[stock].last<context.portfolio.positions[stock].avg_price*context.stoplossmultipler:# 现价低于 原价一定比例\n",
    "            order_target_percent(stock,0)\n",
    "        elif bar_dict[stock].last>context.portfolio.positions[stock].avg_price*context.takepofitmultipler:# 现价高于原价一定比例\n",
    "            order_target_percent(stock,0)\n",
    "\"\"\"\n",
    "config = {\n",
    "  \"base\": {\n",
    "    \"start_date\": \"2000-06-01\",\n",
    "    \"end_date\": \"2016-12-01\",\n",
    "    \"securities\": ['stock'],\n",
    "    \"stock_starting_cash\": 100000,\n",
    "    \"benchmark\": \"000300.XSHG\",\n",
    "#     \"strategy_file_path\": os.path.abspath(__file__)\n",
    "  },\n",
    "  \"extra\": {\n",
    "    \"log_level\": \"verbose\",\n",
    "  },\n",
    "  \"mod\": {\n",
    "    \"sys_analyser\": {\n",
    "#       \"report_save_path\": '.',\n",
    "      \"enabled\": True,\n",
    "      \"plot\": True\n",
    "    }\n",
    "  }\n",
    "}\n",
    "\n",
    "run_code(code, config)"
   ]
  }
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